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MATLAB英文原版课件

Displaying output data: 1.Leave the semicolon off the end of statement. The default format It shows four digits after the decimal point. If the number is too large or too small, it is displayed in scientific notation with an exponent.
2.Disp function num2str: convert a number to a string int2str: covert an integer to a string
3.The fprintf function: be similar with C language Limitation: it only displays the real portion of a complex value
The regulation of variable name: It must begin with a letter, followed by any combination of letters, numbers and the underscore character.
Programming practice: Always give your variables descriptive and easy-to-remember names.
Special values: pi i,j Inf NaN: Not-a-Number eps ans Never redefine the meaning of a predefined variable in MATLAB, it produces subtle and hard-to-find bugs. Quiz 2.2 P38 1, 2, 3 0/0

matlab算法英文教材

matlab算法英文教材
有很多关于MATLAB算法的英文教材可供选择。

以下是几本比较受欢迎的教材：
1. "MATLAB for Engineers: Practical Real-World Applications" by William H. Press, Saul A. Teukolsky, William T. Vetterling, and Brian P. Flannery。

这本书介绍了MATLAB算法和编程技术，包括数值计算、矩阵操作、数据分析等方面的内容，非常适合工程技术人员学习。

2. "MATLAB: A Practical Introduction to Programming and Problem Solving" by John W. Eaton and Donald G. Bates。

这本书是MATLAB编程的入门教材，适合初学者使用。

它介绍了MATLAB的基本语法和算法，包括循环、条件语句、数组和矩阵操作等内容。

3. "The MathWorks MATLAB Guide: A Comprehensive Reference for All Users" by The MathWorks。

这本书是MATLAB编程的全面指南，详细介绍了MATLAB的所有功能和算法。

它包括了MATLAB的各个方面，从基本的语法到高级的编程技术，是一本非常全面的参考书。

这些教材都提供了丰富的例子和练习题，可以帮助读者更好地理解和掌握MATLAB算法。

同时，它们也是学习MATLAB编程和算法的优秀资源。

[MATLAB图书合集].Numerical.Simulation.of.Optical.Wave.

Numerical Simulation of Optical Wave PropagationWith examples in MATLAB®Library of Congress Cataloging-in-Publication DataSchmidt, Jason Daniel, 1975-Numerical simulation of optical wave propagation with examples in MATLAB / Jason D. Schmidt.p. cm. -- (Press monograph ; 199)Includes bibliographical references and index.ISBN 978-0-8194-8326-31. Optics--Mathematics.2. Wave-motion, Theory of--Mathematical models.3. MATLAB. I. Title.QC383.S36 2010535'.42015118--dc222010015089Published bySPIEP.O. Box 10Bellingham, Washington 98227-0010 USAPhone: +1 360.676.3290Fax: +1 360.647.1445Email: Books@Web: Copyright © 2010 Society of Photo-Optical Instrumentation Engineers (SPIE)All rights reserved. No part of this publication may be reproduced or distributed in any form or by any means without written permission of the publisher.The content of this book reflects the work and thoughts of the author(s).Every effort has been made to publish reliable and accurate information herein, but the publisher is not responsible for the validity of the information or for any outcomes resulting from reliance thereon.Printed in the United States of America.About the cover: 50-watt laser for generating mesospheric sodium guide stars over 90 km above the ground. In operation at the Air Force Research Laboratory's 3.5-m telescope at the Starfire Optical Range, Kirtland AFB, NM. (Robert Q. Fugate, © 2005, Albuquerque, NM).Numerical Simulation of Optical Wave PropagationWith examples in MATLAB®Jason D. SchmidtBellingham, Washington USAContentsPreface (ix)Chapter 1 Foundations of Scalar Diffraction Theory (1)1.1 Basics of Classical Electrodynamics (1)1.1.1 Sources of electric and magnetic fields (2)1.1.2 Electric and magnetic fields (2)1.2 Simple Traveling-Wave Solutions to Maxwell's Equations (5)1.2.1 Obtaining a wave equation (5)1.2.2 Simple traveling-wave fields (7)1.3 Scalar Diffraction Theory (9)12............................................................................................Problems1.4Chapter 2 Digital Fourier Transforms (15)2.1 Basics of Digital Fourier Transforms (15)2.1.1 Fourier transforms: from analytic to numerical (15)2.1.2 Inverse Fourier transforms: from analytic to numerical (17)2.1.3 Performing discrete Fourier transforms in software (18)2.2 Sampling Pure-Frequency Functions (21)2.3 Discrete vs Continuous Fourier Transforms (23)2.4 Alleviating Effects of Discretization (26)2.5 Three Case Studies in Transforming Signals (30)Sincsignals (30)2.5.12.5.2 Gaussian signals (31)2.5.3 Gaussian signals with quadratic phase (33)2.6 Two-Dimensional Discrete Fourier Transforms (35)37............................................................................................Problems2.7Chapter 3 Simple Computations Using Fourier Transforms (39)39......................................................................................Convolution3.143........................................................................................3.2Correlation3.347Functions............................................................................Structure50........................................................................................Derivatives3.43.5 Problems (53)Chapter 4 Fraunhofer Diffraction and Lenses (55)4.1 Fraunhofer Diffraction (55)4.2 Fourier-Transforming Properties of Lenses (58)4.2.1 Object against the lens (59)4.2.2 Object before the lens (59)4.2.3 Object behind the lens (61)4.3 Problems (64)Chapter 5 Imaging Systems and Aberrations (65)65........................................................................................5.1Aberrations5.1.1 Seidel aberrations (66)5.1.2 Zernike circle polynomials (66)5.1.2.1 Decomposition and mode removal (73)5.1.2.2 RMS wavefront aberration (75)5.2 Impulse Response and Transfer Function of Imaging Systems (77)5.2.1 Coherent imaging (77)5.2.2 Incoherent imaging (79)5.2.3 Strehl ratio (82)............................................................................................84Problems5.3Chapter 6 Fresnel Diffraction in Vacuum (87)6.1 Different Forms of the Fresnel Diffraction Integral (88)6.2 Operator Notation (89)6.3 Fresnel-Integral Computation (90)6.3.1 One-step propagation (90)6.3.2 Two-step propagation (92)6.4 Angular-Spectrum Propagation (95)6.5 Simple Optical Systems (102)6.6 Point Sources (107)..........................................................................................113 Problems6.7Chapter 7 Sampling Requirements for Fresnel Diffraction (115)7.1 Imposing a Band Limit (115)7.2 Propagation Geometry (117)7.3 Validity of Propagation Methods (120)7.3.1 Fresnel-integral propagation (120)7.3.1.1 One step, fixed observation-plane grid spacing (120)7.3.1.2 Avoiding aliasing (121)7.3.2 Angular-spectrum propagation (124)7.3.3 General guidelines (128)7.4 Problems (130)Chapter 8 Relaxed Sampling Constraints with PartialPropagations (133)8.1 Absorbing Boundaries (134)8.2 Two Partial Propagations (135)8.3 Arbitrary Number of Partial Propagations (138)8.4 Sampling for Multiple Partial Propagations (139)8.5 Problems (146)Chapter 9 Propagation through Atmospheric Turbulence (149)9.1 Split-Step Beam Propagation Method (149)9.2 Refractive Properties of Atmospheric Turbulence (150)9.2.1 Kolmogorov Theory of turbulence (152)9.2.2 Optical propagation through turbulence (156)9.2.3 Optical parameters of the atmosphere (157)9.2.4 Layered atmosphere model (164)9.2.5 Theory (164)9.3 Monte-Carlo Phase Screens (166)9.4 Sampling Constraints (172)9.5 Executing Properly Sampled Simulation (174)9.5.1 Determine propagation geometry and turbulenceconditions (174)9.5.2 Analyze the sampling constraints (176)9.5.3 Perform a vacuum simulation (178)9.5.4 Perform the turbulent simulations (179)9.5.5 Verify the output (180)9.6 Conclusion (182)9.7 Problems (183)Appendix A Function Definitions (185)Appendix B MATLAB Code Listings (187)References (189)Index (195)PrefaceDiffraction is a very interesting and active area of optical research.Unfortunately, analytic solutions are rare in many practical problems,particularly when optical waves propagate through randomlyﬂuctuating media.For many of these problems, researchers must resort to numerical solutions.Still,simulations in optical diffrac-tion are ually,these simulations take advantage of discrete Fourier transforms,which means using discretely spaced samples on aﬁnite-sized grid. This leads to a few tradeoffs in speed and memory versus accuracy.Thus,the pa-rameters of the sampling grids must be chosen very carefully.Some people seek to fully automate those choices,but this cannot be done automatically in every case. To determine grid properties,one must carefully consider computational speed, available computer memory,the Nyquist sampling criterion,geometry,accurate representation of source apertures,and impact on the propagatedﬁeld’s quantities of interest.This book grew out of an independent study I did while I was a doctoral student at University of Dayton.The study was directed by LtCol Matthew Goda,then a professor at the Air Force Institute of Technology(AFIT).After the independent study was over,Goda then created a course at AFIT on wave-optics simulations. When I graduated,I became a professor at AFIT while Goda moved on to a new military assignment.When I began teaching the wave-optics simulation course, there was no book written to the level of detail required for a graduate course fo-cused on wave-optics simulations and sampling requirements.The course was al-ways taught out of the professor’s notes,originally compiled by piling these notes was no small feat,and Goda did a tremendous job combining material from books on discrete Fourier transforms,optics journal articles and conference proceedings,technical reports from companies like the Optical Sciences Company and MZA Associates Corporation,and private communication with researchers.Until this book,simulations have always been an afterthought in just a few books on image processing and nonlinear optics.Clearly there was a gap between the practical knowledge required to perform wave-optics simulations and the the-oretical material covered in great Fourier-optics textbooks like those by Joseph Goodman and Jack Gaskill.I have heard professors across the U.S.talk about how they include material on simulations in their graduate Fourier-optics courses.I ap-plaud them for that effort because it is challenging to teach students both the the-ory and practical simulation of Fourier optics in one course.However,if the stu-ixdents are to become capable enough to write wave-optics simulations for thesis or dissertation research and beyond,they cannot get enough detail in a one-term Fourier-optics course.This is why AFIT has separate courses on Fourier optics and wave-optics simulations.This book is intended for graduate students in programs like physics,electrical engineering,electro-optics,or optical science.The book gives all of the relevant equations from Fourier optics,but to fully understand and appreciate the material, it is important to have a thorough understanding of Fourier optics before reading this book.I believe that part of the beneﬁt of this book is the use of speciﬁc code examples, rather than just pseudo-code.However,the programming or scripting language for the examples needs to be one that is widely used and easy to understand by those who do not already use it.For those reasons,I have used M ATLAB in all of the examples throughout this book.It is heavily used in engineering both at universities and research institutions.Further,it is easy to read because of its simple language and because many numerical algorithms,such as discrete Fourier transforms and convolution,are part of its basic library.If I used other languages like C,C++, FORTRAN,Java,and Python,I would need to pick a particular external library of numerical routines or write my own algorithms and include them in the book.I believe that using M ATLAB in this book allows readers to focus on the wave propagation,rather than the most basic numerical algorithms like discrete Fourier transforms.Further,any user with access to the M ATLAB interpreter can execute the code examples as shown.No additional libraries need to be acquired and installed. Moreover,my examples rarely use M ATLAB’s toolboxes,relying heavily on its basic functionality.Readers should note that the code examples used throughout the book are designed for conceptual simplicity,rather than optimized for speed or memory usage.I encourage readers to rework my M ATLAB examples to achieve greater performance or even implement them in other languages.I offer my thanks and appreciation to all those who have paved the way for this work,particularly Glenn Tyler,David Fried,and Phillip Roberts at the Optical Sciences Company and Steve Coy at MZA Associates Corporation.In1982,Fried and Tyler wrote a technical report describing methods of simulating optical wave propagation and related sampling constraints.A few years later,Roberts wrote a follow-on report giving another clear,nicely detailed description of one-step,two-step,and angular spectrum propagation methods.More recently,Coy wrote a tech-nical report that gives a very nice description of the relationship between sampling requirements propagation geometry.These reports formed the beginnings of Goda’s notes and eventually this book.Also,thanks to those who answered my questions about wave-optics simula-tions while I was a student at UD and then while I taught the wave-optics simula-tion course as a professor at AFIT:Jeffrey Barchers,Troy Rhoadarmer,Terry Bren-nan,and Don Link.These gentlemen are experienced and accomplished researcherswhose advice was very much appreciated.Additionally,thanks to Michael Havrilla for his help with the basic electrodynamics in Ch.1.Special thanks to Matthew Goda for his foundational work in the course and its notes.Without him,this book would not be possible.He made much of the material in this book accessible to dozens of students who went on to do great things for the U.S.Air Force.Finally,I’d like to thank all those students who helpedﬁnd errors in the drafts of this book and whose inquisitive nature caused me to reﬁne and add material along the way.Jason SchmidtJune,2010Chapter1Foundations of Scalar Diffraction TheoryLight can be described by two very different approaches:classical electrodynam-ics and quantum electrodynamics.In the classical treatment,electric and magnetic ﬁelds are continuous functions of space and time,and light comprises co-oscillating electric and magnetic waveﬁelds.In the quantum treatment,photons are elemen-tary particles with no mass nor charge,and light comprises one or more photons. There is rigorous theory behind each approach,and there is experimental evidence supporting both.Neither approach can be dismissed,which leads to the wave-particle duality of light.Generally,classical methods are used for macroscopic properties of light,while quantum methods are used for submicroscopic proper-ties of light.This book describes macroscopic properties,so it deals entirely with classi-cal electrodynamics.When the wavelengthλof an electromagnetic wave is very small,approaching zero,the waves travel in straight lines with no bending around the edges of objects.That is realm of geometric optics.However,this book treats many situations in which geometric optics are inadequate to describe observed phe-nomena like diffraction.Therefore,the starting point is classical electrodynamics with solutions provided by scalar diffraction theory.Geometric optics is treated brieﬂy in Sec.6.5.1.1Basics of Classical ElectrodynamicsClassical electrodynamics deals with relationships between electricﬁelds,magnetic ﬁelds,static charge,and moving charge(i.e.,current)in space and time based on the macroscopic properties of the materials in which theﬁelds exist.We deﬁne each quantity here along with some basic relationships.This introduces the reader to the quantities in Maxwell’s equations,which describe how electrically charged particles and objects give rise to electric and magneticﬁelds.Maxwell’s equations are introduced here in their most general form,and then the discussion focuses on a speciﬁc case and solutions for oscillating electric and magneticﬁelds,which light comprises.12Chapter 11.1.1Sources of electric and magneticﬁeldsElectric charge,measured in coulombs,is a fundamental property of elementary particles and bulk materials.Classically,charge may be positive,negative,or zero. Further,charge is quantized,speciﬁcally the smallest possible nonzero amount of charge is the elementary charge e=1.602×10−19C.All nonzero amounts of charge are integer multiples of e.For bulk materials,the integer may be very large so that total charge can be treated as continuous rather than discrete.We denote the volume density of free charge,measured in coulombs per cubic meter,byρ(r,t), where r is a three-dimensional spatial vector,and t is time.Moving charge density is called free volume current density J(r,t).V olume current density is measured in Ampères per square meter(1A=1C/s).This represents the time rate at which charge passes through a surface of unit area.Finally,charge is conserved,meaning that the total charge of any system is constant.This is mathematically stated by the continuity equation=0.(1.1)∇·J(r,t)+∂ρ(r,t)∂tAlmost every material we encounter in life is composed of many,many atoms each with many positive and negative ually,the numbers of positive and negative charges are equal or nearly equal so that the whole material is electrically neutral.Still,such a material can give rise to electric or magneticﬁelds when the to-tal charge and free current are zero.If the distribution of charge is not homogeneous or if the charges are circulating in tiny current loops,ﬁelds could be present.The separation of charge is described by the electric dipole moment,which is the amount of separated charge times the separation distance.If a bulk material has its charge arranged in many tiny dipoles,it is said to be electrically polarized.The volume polarization density P(r,t)is the density of electric dipole moments per unit volume,measured in coulombs per square meter.Magnetization is a similar concept for moving charge.Charge circulating in a tiny current loop is described by magnetic dipole moment,which is the circulat-ing current times the area of the loop.When a bulk material has internal current arranged in many tiny loops,it is said to be magnetized.The volume magnetiza-tion density M(r,t)is the density of magnetic dipole moments per unit volume, measured in Ampères per meter.1.1.2Electric and magneticﬁeldsWhen a hypothetical charge,called a test charge,passes near a bulk material that has non-zeroρ,J,P,or M,the charge experiences a force.This interaction is char-acterized by two vectors E and B.The electromagnetic force F on a test particle at a given point and time is a function of these vectorﬁelds and the particle’s charge q and velocity v.The Lorentz force law describes this interaction asF=q(E+v×B).(1.2)If this empirical statement is valid(and,of course,countless experiments over the course of centuries have shown that it is),then two vectorﬁelds E and B are thereby deﬁned throughout space and time,and these are called the“electricﬁeld”and “magnetic induction.”1Eq.(1.2)can be examined in a little more detail to provide more intuitive deﬁni-tions of theseﬁelds.The electricﬁeld is the amount of force per unit of test charge when the test charge is stationary,given byE=limq→0+Fq v=0.(1.3)This is called a push-and-pull force because the force is in either the same or op-posite direction as theﬁeld,depending on the sign of the charge.Electricﬁeld is measured in units of volts per meter(1V=1N m/C).The magneticﬁeld is related to the amount of force per unit test charge given byv×B=limq→0+F−q Eq v=0.(1.4)The force due to a magneticﬁeld is called deﬂective because it is perpendicular to the particle’s velocity,which deﬂects its trajectory.Magneticﬁeld is measured in units of Tesla[1T=1N s/(C m)].With this understanding of theﬁelds,they now need to be related to the sources. This was accomplished through centuries of experimental measurements and theo-retical and intuitive insight,resulting in∇×E+∂B∂t=0(1.5)∇×B−µ0 0∂E∂t=µ0 J+∂P∂t+∇×M .(1.6)These are two of Maxwell’s equations,the former being Faraday’s law and the latter being Ampère’s law with Maxwell’s correction.In Eq.(1.6),the sources on the right hand side include the free current J and two terms due to bound currents. These are the polarization current∂P/∂t and the magnetization current∇×M.These equations can be written in a more functionally useful form.Eq.(1.6) can be rewritten as∇× Bµ0−M =J+∂∂t( 0E+P).(1.7) Making the deﬁnitionsD= 0E+P(1.8)H=Bµ0−M(1.9)Foundations of Scalar Diffraction Theory3introduces the concepts of electric displacement D and magnetic ﬁeld H ,which are ﬁelds that account for the medium’s response to the applied ﬁelds.Now,the working form of these Maxwell equations becomes∇×E =−∂B∂t (1.10)∇×H =J +∂D ∂t .(1.11)Further,when these are combined with conservation of charge expressed in Eq.(1.1),this leads to∇·∇×H =∇·J +∂∂t ∇·D (1.12)=−∂ρ∂t +∂∂t∇·D (1.13)=0.(1.14)Focusing on the right-hand side,∂∂t(∇·D −ρ)=0(1.15)∇·D −ρ=f (r ),(1.16)where f (r )is an unspeciﬁed function of space but not time.Causality requires that f (r )=0before the source is turned on,yielding Coulomb’s law:∇·D =ρ.(1.17)Similar manipulations yield∇·B =0.(1.18)This indicates that magnetic monopole charges do not exist.Finally,Eqs.(1.10),(1.11),(1.17),and (1.18)constitute Maxwell’s equations.1In this model of macroscopic electrodynamics,Eqs.(1.10)and (1.11)are two independent vector equations.With three scalar components each,these are six in-dependent scalar equations.Unfortunately,given knowledge of the sources,there are four unknown vector ﬁelds D ,B ,H ,and E .Each has three scalar components for a total of twelve unknown scalars.With so many more unknown ﬁeld compo-nents than equations,this is a poorly posed problem.The key is to understand the medium in which the ﬁelds exist.This produces a means of relating P to E and M to H ,which amount to six more scalar equations.For example,in simple media (linear,homogeneous,and isotropic),P = 0χe E(1.19)M =χm H ,(1.20)4Chapter 1Foundations of Scalar Diffraction Theory5 whereχe is the electric susceptibility of the medium andχm is its magnetic sus-ceptibility.Substituting these into Eqs.(1.8)and(1.9)yieldsD= 0E+P(1.21)= 0(1+χm)E(1.22)= E(1.23) andB=µ0(H+M)(1.24)=µ0(1+χm)H(1.25)=µH,(1.26) where =(1+χe) 0is the electric permittivity andµ=(1+χm)µ0is the magnetic permeability of the medium.Now,this simpliﬁes Eqs.(1.10)and(1.11) so that∇×E=−µ∂H∂t(1.27)∇×H=J+ ∂E∂t.(1.28) Now,there are still six equations but only six unknowns(as long as the free current density J is known).Finally,with a proper understanding of the materials,this is a well posed problem.1.2Simple Traveling-Wave Solutions to Maxwell’s Equations There are many solutions to Maxwell’s equations,but there are only a few that can be written in closed form without an integral.This section begins with transforming Maxwell’s four equations into two uncoupled wave equations.It continues with a few speciﬁc simple solutions such as the inﬁnite-extent plane wave.A more general solution is left to the next section.1.2.1Obtaining a wave equationThis book deals with optical wave propagation through linear,isotropic,homoge-neous,nondispersive,dielectric media in the absence of source charges and cur-rents.In this case,the media discussed throughout the remainder of this book have=a scalar,independent ofλ,r,t(1.29)µ=µ0(1.30)ρ=0(1.31)J=0.(1.32)Taking the curl of Eq.(1.27)yields∇×(∇×E )=−µ0∂∂t (∇×H ).(1.33)Then,substituting in Eq.(1.28)gives∇×(∇×E )=−µ0 ∂2∂t 2E .(1.34)Now,applying the vector identity ∇×(∇×E )=∇(∇·E )−∇2E leads to∇(∇·E )−∇2E =−µ0 ∂2∂t 2E .(1.35)Finally,substituting in Eqs.(1.17)and (1.23),and keeping in mind that is inde-pendent of position results in a wave differential equation:∇2E −µ0 ∂2∂t 2E =0.(1.36)Similar manipulations beginning with the curl of Eq.(1.28)yield∇2B −µ0 ∂2∂t 2B =0.(1.37)When the Laplacian is used on the Cartesian components of E and B ,the result is six uncoupled but identical equations of the form∇2−µ0 ∂2∂t2 U (x,y,z )=0,(1.38)where the scalar U (x,y,z )stands for any of the x -,y -or z -directed components of the vector ﬁelds E and B .At this point,we can deﬁne index of refraction n = 0(1.39)and the vacuum speed of light c =1√µ0 0(1.40)so that∇2−n 2c 2∂2∂t 2 U (x,y,z )=0.(1.41)The electric and magnetic ﬁelds that compose light are traveling wave ﬁelds.There-fore,ﬁelds with harmonic time dependence exp (−i 2πνt )(where νis the wave 6Chapter 1frequency)are the types of solutions sought for the purposes of this book.When this is substituted into Eq.(1.41),the result is∇2+ 2πnνc 2 U=0.(1.42) Typically,the wavelength is given byλ=c/ν,and the wavenumber is deﬁned as k=2π/λso that ∇2+k2n2 U=0.(1.43) This is the Helmholtz equation,and it appears in many other branches of physics including thermodynamics and quantum mechanics.At this point,we can dispense with the time dependence since it is the same for all solutions of the Helmholtz equation.From this point forward,theﬁeld U(x,y,z)refers to the phasor por-tion of the opticalﬁeld(i.e,no time dependence).Further,we deﬁne the units of U(x,y,z)to be square-root watts per meter(1W=1J/s=1N m/s)so that optical irradiance I=|U|2is in units of watts per meter squared.The value of the electric ﬁeld or magnetic induction can always be obtained by a simple conversion of units.1.2.2Simple traveling-waveﬁeldsThere are several simple traveling-waveﬁelds that are useful in this book.These are planar,spherical,and Gaussian-beam waves.With each of these solutions,theﬁeld at all points always maintains its planar,spherical,or Gaussian-beam form,and pa-rameters like radius of curvature change in a simple manner as the wave propagates. The next section on scalar diffraction theory handles more general cases.A planar wave is the simplest possible traveling wave.It has uniform amplitude and phase in any plane perpendicular to its direction of propagation.More gener-ally,when the optical axis is not along the direction of propagation,a planar wave ﬁeld is given byU P(r)=A exp(i k·r),(1.44) where A is the amplitude of the wave andk=2πλ(αˆx+βˆy+γˆz)(1.45)is the wavevector with direction cosines given byα,β,andγ.Then,making the direction cosines more explicit,U P(r)=A exp i2πλ(αx+βy+γz) .(1.46)This wave travels at an angle cos−1αfrom the x-axis and cos−1βfrom the y-axis as shown in Fig.1.1.Foundations of Scalar Diffraction Theory7yzFigure 1.1Depiction of direction cosines α,β,and γ.A spherical wave is the next simplest wave ﬁeld.It has a wavefront that is spherical in shape,and it is either diverging or converging.The energy of the wave is spread uniformly over a spherical surface with area given by 4πR 2,where R is the wavefront radius of curvature.Conservation of energy requires that the ampli-tude is accordingly proportional to R −1.A spherical wave is given byU S (r )=A exp [ikR (r )]R (r ).(1.47)If the center of the sphere is located at r c =(x c ,y c ,z c ),then at an observation point r =(x,y,z ),the radius of curvature is given by R (r )= (x −x c )2+(y −y c )2+(z −z c )2.(1.48)Often in optics,attention is restricted to regions of space that are very close to the optical axis.This is called the paraxial approximation,and assuming propagation in the positive z direction,this approximation is mathematically written ascos −1α 1(1.49)cos −1β 1.(1.50)With this approximation,we eliminate the square root by expanding it as a Taylor series and keeping only the ﬁrst two terms,yielding R (r ) ∆z 1+12 x −x c ∆z 2+12 y −y c ∆z2 ,(1.51)where we have deﬁned ∆z =|z −z c |.With the paraxial approximation,a spherical wave is approximatelyU S (r ) A e ik ∆z ∆z e i k 2∆z [(x −x c )2+(y −y c )2].(1.52)8Chapter 1Oneﬁnal simple traveling wave often encountered in optics is the Gaussian-beam wave.It has a Gaussian amplitude proﬁle and“paraxially spherical”wave-front.The full derivation of the Gaussian-beam solution invokes the paraxial ap-proximation along the way.Such a derivation can be found in common laser text-books like Refs.2–3.This solution is given byU G(r)=Aq(z)exp ik x2+y22q(z) ,(1.53)where1 q(z)=1R(z)+iλπW2(z)(1.54)and the beam radius and wavefront radius of curvature are given byW2(z)=W20 1+ λzπW20 2 (1.55)R(z)=z 1+ πW20λz 2 ,(1.56)where W0is the minimum spot radius.At any point along the z axis,W(z)is the 1/e radius of theﬁeld amplitude.Also,by this convention,W(0)=W0so that the minimum spot radius is located at z=0.1.3Scalar Diffraction TheoryOften,the optical source is not a simple planar,spherical,nor Gaussian-beam wave. For more general cases,we must use more sophisticated means to solve the scalar Helmholtz equation.This means taking advantage of Green’s theorem with clever use of boundary conditions.This process is not discussed in detail here,but the interested reader should consult books like Refs.4–5for a detailed treatment.The geometry for this more general case is shown in Fig.1.2.In thisﬁgure, the coordinates are r1=(x1,y1)in the source plane and r2=(x2,y2)in the observation plane.The distance between the two planes is∆z.Theﬁgure illus-trates the basic problem:given the source-plane opticalﬁeld U(x1,y1),what is the observation-planeﬁeld U(x2,y2)?The solution is given by the Fresnel diffraction integralU(x2,y2)=e ik∆ziλ∆z∞−∞∞−∞U(x1,y1)e i k2∆z[(x1−x2)2+(y1−y2)2]dx1dy1.(1.57)Note that this is not the most general solution.In fact,it is a paraxial approximation, but it is general enough and accurate enough for the purposes of this book. Foundations of Scalar Diffraction Theory9。

matlab教程电子书01

用surf和shading interp绘图
用mesh绘图
用mesh和隐藏线绘图
用contour绘图
图1-2 四种方法绘制双变量的一个函数的图形
下载
(c) MATLAB也能绘制一条参数曲线，例如：
x-y平面图如图 1-3所示。
3 第1章 MATLAB是什么
图1-3 一个参数曲线图 ■
■ 例1.2 函数分析 MATLAB命令fzero和fmin可以用于寻找一个函数的零点和最小值。函数 xex2 − ex2 − sin x3 可以用名叫 func的用户自定义函数 (见2.9节)表示，并存入一个名叫
% p 1 = A向量等于一次多项式的系数。 % linc=A向量等于x点上多项式 p1的值。 % 绘制多项式和由‘ x’标记的数据。
结果见图1-5(左图)。能以最小二乘法对一组点拟合高次多项式。对上面的命令行进行一点小改动就可以得到 7 次多项式：
p7=polyfit(x, y, 7); xx=1:0.25:8; polc=polyval(p7, xx); p l o t = ( x x , p o l c , x , ’y ,x’)
■ 例1.1 二维和三维函数
MATLAB能用于计算，并以二维和三维图形显示各种函数。在 MATLAB函数中包括了所
有主要的数学函数和大量的高级函数。
(a) 用简短的 MATLAB命令计算并绘制在 0≤x≤6范围内的 sin(2x)、sinx2和sin2x。
x=linspace(0,6); y1=sin(2*x); y2=sin(x.^2); y3=(sin(x)).^2;
% 创建一个向量 x。 % 向量y1等于x坐标上某一 x的sin(2x)值。 % 向量y2等于sin(x.^2)，同上。 % 向量y3等于(sin(x)).^2，同上。

MATLAB英文手稿讲义References

References1. Wang Yonglong, Introduction and Applications in MATLAB (manuscript), 2007.2. Rudra Pratap. Getting Started with MATLAB 5: A Quick Introduction for Scientists and Engineers, 1999, Oxford University.3. Cheng Weiguo, Feng Feng, Wang Xuemei, and Liu Yi. Advanced Applications on MATLAB 5.3 Programming, China Machine Press, 2000.(程卫国，冯峰，王雪梅，刘艺，MATLAB 5.3 精要、编程及高级应用，2000，机械工业出版社.)4. Adrian Biran, Moshe Breiner. MATLAB 6 for Engineers, New York: Prentice Hall, 2002.5. Edward B. Magrab etal.. An Engineer’s Guide to MATLAB, Publishing House of Electronics Industry, 2002 (in Chinese).6. Delores M. Etter, David C. Kuncicky, Dug Hull. Introduction to MATLAB 6. 2nd ed., NJ: Pearson Education Inc, 2004.7. Help Contents of MATLAB 7.1.8. Liu Weiguo. MATLAB Program and Application (Second Edition), Higher Education Press, 2006. (in Chinese)(刘卫国主编. MATLAB程序设计与应用(第二版),高等教育出版社，2006.)9. . MATLAB Application, Publishing House of Electronics Industry, 2005. (in Chinese)(飞思科技产品研发中心编著. MATLAB7 基础与提高，电子工业出版社，2005.)10. John H. Mathews, and Kurtis D. Fink. Numerical Methods Using MATLAB (4th Edition), Publishing House of Electronics Industry, 2005.11. Stephen J. Chapman. MATLAB Programming for Engineers (Second Edition), Science Press (Beijing), 2005.12. Peng Fanglin. Solutions and Visualizations of Mathematical Physical Equations in MATLAB, Tsing Hua University Press, 2004 (in Chinese).(彭芳麟. 数学物理方程的MATLAB解法与可视化，清华大学出版社，2004.)13. Help Contents of MATLAB 7.1.14. Qiu Guanyuan. Electrocircuits, Higher Education Press, 2004. (in Chinese)(邱关源，电路，高等教育出版社，2004.)15. Chen Xiaoping, Li Changjie. MATLAB and Applications in Electrocircuits and Automatic Control, University of Science and Technology of China Press, 2004(in Chinese).(陈晓平，李长杰，MATLAB及其在电路与控制理论中的应用，中国科学技术大学出版社，2004.)16 Richard Feynman. Lectures on Physics, World Publishing Company, 2005.17. Zhong Jikang, Bao Hongji. Computer Solutions to the Problems of College Physics, Applications of MATLAB Programming, China Machine Press, 2007.(in Chinese)(钟季康，鲍鸿吉. 大学物理习题计算机解法，MATLAB编程应用，机械工业出版社，2007.)233。

matlab中文电子书汇集

《MATLAB数据处理与应用》/bbs/viewthread.php?tid=8787743&extra=&page=1《战胜MATLAB必做练习50题》--满晓宇/罗捷--北京大学出版社--2001-11，/bbs/viewthread.php?tid=8684485&highlight=matlabmatlab学习指导教程/bbs/viewthread.php?tid=9077453&highlight=matlab《Matlab宝典》/bbs/viewthread.php?tid=8787742&highlight=matlabMATLAB命令大全.pdf，/bbs/viewthread.php?tid=8872051&highlight=matlabMATLAB函数速查手册DOC文档，/bbs/viewthread.php?tid=9036014&highlight=matlabmatlab聚类工具箱教程，/bbs/viewthread.php?tid=8858415&highlight=matlabMATLAB高效编程技巧与应用25个案例分析,/bbs/viewthread.php?tid=9062882&highlight=matlab《MATLAB 遗传算法工具箱与应用》---雷英杰，/bbs/viewthread.php?tid=8787725&highlight=matlab《基于MATLAB的系统分析与设计- - -模糊系统》---楼顺天---西安电子科技大学出版社, /bbs/viewthread.php?tid=8666654&highlight=matlab自动控制：反馈的力量——使用MATLAB---特费斯---西安交通大学出版社/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB高级语言及其在控制系统中的应用---韩九强---西安交通大学出版社---1997年06月第1版/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB有限元分析与应用---P.I.Kattan---清华大学出版社----2004-04-01,版次:1/bbs/viewthread.php?tid=8666654&highlight=matlab反馈控制问题:使用MATLAB及其控制系统工具箱---（美）弗雷德里克（Frederick,D.K.），（美）周（Chow,J.H.），张彦斌译----西安交大,/bbs/viewthread.php?tid=8666654&highlight=matlab先进PID控制及其MATLAB仿真---刘金琨著----电子工业出版社/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB语言工具箱---施阳...[等]编著---西北工业大学出版社/bbs/viewthread.php?tid=8666654&highlight=matlabMatlab工具箱应用指南——应用数学篇---李涛贺勇军刘志俭等----电子工业出版社---2000年05月第1版/bbs/viewthread.php?tid=8666654&highlight=matlab模糊控制及其MATLAB应用---张国良... [等] 著---西安交通大学出版社/bbs/viewthread.php?tid=8666654&highlight=matlab基于MATLAB的系统分析与设计——时频分析---胡昌华等编著---西安电子科技大学出版社----2001-7 ,印次: 1/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB语言与自动控制系统设计---魏克新等编---机械工业出版社---2001-05-01,版次:1 /bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB语言与控制系统仿真---孙亮主编---北京工业大学出版社---2005-01-07,版次:1/bbs/viewthread.php?tid=8666654&highlight=matlabMatLab工程数学应用---许波/等主编：雷洪勤/等---清华大学出版社--2000-12-01 ,版次:1 /bbs/viewthread.php?tid=8666654&highlight=matlab系统辨识及其MATLAB仿真---侯媛彬等编著/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB 6.5辅助优化计算与设计---飞思科技产品研发中心编著---电子工业出版社---2003 /bbs/viewthread.php?tid=8666654&highlight=matlabMatlab工具箱应用指南控制工程篇---李涛,徐昕,伯晓晨编著---电子工业出版社--- 2000-05-01/bbs/viewthread.php?tid=8666654&highlight=matlab偏微分方程的MATLAB解法---陆君安尚涛谢进----武汉大学出版社---2001-8-1/bbs/viewthread.php?tid=8666654&highlight=matlab科学计算自由软件——SCILAB教程---胡包钢, 赵星, 康孟珍编著----清华大学出版社----2003-06-30/bbs/viewthread.php?tid=8666654&highlight=matlab系统仿真分析与设计:MATLAB语言工程应用----国防科大----2001-12-01/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB 6.5辅助神经网络分析与设计----飞思科技产品研发中心编著---电子工业出版社---2003/bbs/viewthread.php?tid=8666654&highlight=matlab现代线性系统:使用MATLAB ----(美)斯特拉姆,(美)柯克---西安交通大学出版社----2002-05-30 /bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB辅助模糊系统设计---吴晓莉, 林哲辉等编著---西安电子科技大学出版社---2002 /bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB工程计算及应用----李丽王振领编---人民邮电出版社---2001-09-01,版次:1/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB神经网络仿真与应用--闻新等编著---科学出版社---2003-07-01,版次:1/bbs/viewthread.php?tid=8666654&highlight=matlab电路与系统分析--使用MATLAB---赵录怀/杨育霞/张震---高等教育出版----2004-7-1/bbs/viewthread.php?tid=8666654&highlight=matlab控制系统分析、设计和应用:MATLAB语言的应用---何衍庆--化学工业出版社发行部----2003-01-01,版次:1/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB神经网络应用设计---闻新... 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[等] 编著---武汉大学出版社---2002-/bbs/viewthread.php?tid=8666654&highlight=matlab精通SIMULINK系统仿真与控制---沈辉---北京大学出版社---2003-01-01,版次:1/bbs/viewthread.php?tid=8666654&highlight=matlab基于MATLAB的动态模型与系统仿真工具—Simulink 3.0/4.X---邱晓林---西安交通大学出版社---2003-10-01 ,版次:1精通MATLAB 6.5---张瑞丰---中国水利水电出版社---2004-02-01 ,版次:1/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB仿真技术与应用教程---钟麟/王峰---国防工业出版社--- 2004-1-1/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB工具箱应用/MATLAB应用与提高系列---苏金明编---电子工业出版社---2004-01-01 /bbs/viewthread.php?tid=8666654&highlight=matlab数值方法和MATLAB实现与应用(中文) ---Geraldecktenwald ---机械工业出版社/bbs/viewthread.php?tid=8666654&highlight=matlab基于MATLAB/Simulink的系统仿真技术与应用---薛定宇,陈阳泉---清华大学出版社/bbs/viewthread.php?tid=8666654&highlight=matlab普通高等教育“十五”规划教材--交直流调速系统与MATLAB仿真---周渊深---中国电力出版社/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB与SIMULINK工程应用---(法) 莫克塔里, (法) 玛丽著---电子工业出版社---2002-01-01/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB模糊逻辑工具箱的分析与应用--- 闻新/等---科学出版社---1900-1-1/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB符号运算及其应用---黄忠霖, 黄京编著---国防工业出版社---2004-01-01/bbs/viewthread.php?tid=8666654&highlight=matlab神经网络理论与MATLAB7实现---飞思科技产品研发中心---电子工业出版社--- 2005-12-01 ,版次:1/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB及其在电路与控制理论中的应用---陈晓平---中国科学技术大学出版社---2004-09-01 ,版次:1/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB M语言高级编程--- 陈永春编---清华大学出版社/bbs/viewthread.php?tid=8666654&highlight=matlab高等应用数学问题的MATLAB求解---薜定宇，陈阳泉著---清华大学出版社---2004-8 ,印次: 1 /bbs/viewthread.php?tid=8666654&highlight=matlab控制系统MATLAB计算及仿真(21世纪高等院校优秀教材) --- 黄忠霖---国防工业出版社---2004年09月第二版/bbs/viewthread.php?tid=8666654&highlight=matlabMATLAB宝典---陈杰---电子工业出版社---2007/bbs/viewthread.php?tid=8775758&highlight=matlab化学化工中的数学方法及MATLAB实现--- 许国根, 许萍萍编著---2008年/bbs/viewthread.php?tid=8765828&highlight=matlabMatlab的神经网络工具箱实用指南.doc/bbs/viewthread.php?tid=8659427&highlight=matlabMATLAB 6.0时尚创作百例/bbs/viewthread.php?tid=8982968&highlight=matlab神经网络理论与MATLAB7实现/bbs/viewthread.php?tid=9006133&highlight=matlabMATLAB语言在运筹学中的应用.pdfMATLAB基础与编程入门/bbs/viewthread.php?tid=9070472&highlight=matlabMatlab数值计算程序/bbs/viewthread.php?tid=8779459&highlight=matlab图论算法及其MATLAB实现/bbs/viewthread.php?tid=9020676&highlight=matlabmatlab学习专题基础81问/bbs/viewthread.php?tid=9077448&highlight=matlab《高等应用数学问题的MATLAB求解，第二版》/bbs/viewthread.php?tid=9005513&highlight=matlabMATLAB基础与编程入门/bbs/viewthread.php?tid=9070472&highlight=matlabMATLAB编程(第二版)-菜鸟入门教材/bbs/viewthread.php?tid=8962922&highlight=matlab遗传算法及MATLAB实现/bbs/viewthread.php?tid=8769608&highlight=matlabMATLAB高效编程技巧与应用25个案例分析--吴鹏著---北京航空航天大学出版社---2010. /bbs/viewthread.php?tid=9062557&highlight=matlab《MATLAB概率与数理统计分析》/bbs/viewthread.php?tid=9062697&highlight=matlab系统辨识及其MATLAB仿真/bbs/viewthread.php?tid=8882589&highlight=matlab偏微分方程的MATLAB解法PDF/bbs/viewthread.php?tid=8777000&highlight=matlab掌握和精通Matlab/bbs/viewthread.php?tid=8659414&highlight=matlab《Matlab图形图像》苏金明/bbs/viewthread.php?tid=8787731&highlight=matlabMATLAB TLC文件在嵌入式系统中的应用资料/bbs/viewthread.php?tid=8705415&highlight=matlabDsp for Matlab and Labview--Forester W. 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MATLAB命令大全----姚东等+PDF/bbs/viewthread.php?tid=8790152&highlight=matlab Matlab工具箱应用指南—应用数学篇/bbs/viewthread.php?tid=8778816&highlight=matlab 《Matlab扩展编程》----何强/bbs/viewthread.php?tid=8787736&highlight=matlab Matlab simulink在FPGA设计中的应用.pdf/bbs/viewthread.php?tid=8754346&highlight=matlab MATLAB在化学中的应用---许国根，许萍萍，谭宪林---西安交通大学出版社/bbs/viewthread.php?tid=8586003&highlight=matlab matlab 6.5 辅助优化计算与设计飞思科技研发中心编著/bbs/viewthread.php?tid=8787720&highlight=matlab Matlab6.0图形图像处理函数/bbs/viewthread.php?tid=8850876&highlight=matlab MATLAB语言与数学建模/bbs/viewthread.php?tid=8901025&highlight=matlab 官方教材：Matlab7.0学习资料/bbs/viewthread.php?tid=8659402&highlight=matlab Matlab循序渐进/bbs/viewthread.php?tid=8659412&highlight=matlab MATLAB及其在理工课程中的应用/bbs/viewthread.php?tid=8775929&highlight=matlab 精通matlab7.0. 书籍/bbs/viewthread.php?tid=8897467&highlight=matlab 实验设计与统计学－－matlab/bbs/viewthread.php?tid=8890509&highlight=matlab 滑模变结构控制MATLAB仿真/bbs/viewthread.php?tid=8844997&highlight=matlab 基于MATLAB的系统分析与设计——时频分析/bbs/viewthread.php?tid=8707431&highlight=matlabmatlab语言与自动控制系统设计PDF格式/bbs/viewthread.php?tid=8864842&highlight=matlab 用Matlab实现Delaunay剖分和基于剖分的规格化计算/bbs/viewthread.php?tid=8884650&highlight=matlab 数字图像处理Matlab版----冈萨雷斯编----第二版英文版/bbs/viewthread.php?tid=8762467&highlight=matlab LVQ神经网络学习算法的MATLAB实现/bbs/viewthread.php?tid=8869649&highlight=matlab 北师大计算物理习题及解答matlab版/bbs/viewthread.php?tid=8859726&highlight=matlab 精通MATLAB综合辅导与指南例程(word版&程序代码)/bbs/viewthread.php?tid=8629345&highlight=matlab 精通MATLAB—综合辅导与指南/bbs/viewthread.php?tid=8840431&highlight=matlab MATLAB神经网络应用设计----张德丰----机械工业出版社----2009.01 /bbs/viewthread.php?tid=8838695&highlight=matlab MATLAB神经网络应用设计/bbs/viewthread.php?tid=8838823&highlight=matlab matlab—curvefit曲线拟合工具箱手册/bbs/viewthread.php?tid=8655593&highlight=matlab MATLAB模糊系统设计----张德丰------国防工业出版社----2009.04/bbs/viewthread.php?tid=8838832&highlight=matlab MATLAB6.0数学教程/bbs/viewthread.php?tid=8835386&highlight=matlab matlab与vc混合编程，图文解说/bbs/viewthread.php?tid=8835256&highlight=matlab MATLAB5手册-----王艳清孙锋朱群雄等译--机械工业出版社/bbs/viewthread.php?tid=8792400&highlight=matlab Matlab電子電路分析/bbs/viewthread.php?tid=8726133&highlight=matlab 从Matlab/Simulink模型到代码实现----陈永春---清华大学出版社----2002 /bbs/viewthread.php?tid=8830655&highlight=matlab 从Matlab/Simulink模型到代码实现/bbs/viewthread.php?tid=8830711&highlight=matlab 精通MATLAB7.0----王正林刘明----电子工业出版社---2006-8-22，第一版，/bbs/viewthread.php?tid=8809683&highlight=matlab 全息技术资料Optical Scanning Holography with MATLAB/bbs/viewthread.php?tid=8806347&highlight=matlab 机构动态仿真(matlab)】/bbs/viewthread.php?tid=8784425&highlight=matlab。

Matlab入门教程——英文原版

4
1.2 How to read this tutorial In the sections that follow, the MATLAB prompt (») will be used to indicate where the commands are entered. Anything you see after this prompt denotes user input (i.e. a command) followed by a carriage return (i.e. the “enter” key). Often, input is followed by output so unless otherwise specified the line(s) that follow a command will denote output (i.e. MATLAB’s response to what you typed in). MATLAB is case-sensitive, which means that a + B is not the same as ahe ones you just witnessed, will also be used to simulate the interactive session. This can be seen in the example below: e.g. MATLAB can work as a calculator. If we ask MATLAB to add two numbers, we get the answer we expect. » 3 + 4 ans = 7 As we will see, MATLAB is much more than a “fancy” calculator. In order to get the most out this tutorial you are strongly encouraged to try all the commands introduced in each section and work on all the recommended exercises. This usually works best if after reading this guide once, you read it again (and possibly again and again) in front of a computer.

matlab经典资料下载网址

1.张志勇matlab 6.x编程【入门的经典书籍】/d/820aebc188c2365ac01a181f0b043bf45c67539515383c002. MA TLAB5.3精要编程及高级应用作者：程卫国等编著出版社：机械工业出版社/d/dc65cb13b1c5f85791000385469532f6ce30c35c12e09b003. matlab6.5 辅助小波分析与应用飞思科技研发中心编著飞思在线“下载专区”提供书中范例源代码。

/d/95167931363dc5e996f9eb763e26d5c437d0933f6f4d93004.matlab 6.5 辅助优化计算与设计飞思科技研发中心编著/d/28edd9ffc8ab2245c43e2af00c6ac722773a170752cd6d005.matlab6.x 图像处理作者：孙兆林清华大学出版社/d/49488e4bc148e2b4eb794fa2540089eecc88f1b46a9068006.Matlab Programming for Enginners 【英文影印版Stephen J.Chapman】/d/8250bee5c661d84a4465d268ad6bae6d52b736eca556aa00雷英杰《MATLAB 遗传算法工具箱与应用》/d/db42dcbb45415dccdb01c4cb238f4795447de9a9e57f8204王正林《精通Matlab7》/d/ac8a8ab7a2fd76bbec02ccbbc4ff8612bb18a6fd13ba2c01钟麟《Matlab仿真技术与应用教程》/d/0014c6c984e6ce872bcc28d0df84a0c77e25cfe1daa3bb00王立宁《Matlab与通信仿真》/d/128237ae732c7e29fcc1acddc374771ffbc5cad3fdeaf900苏金明《Matlab工具箱应用》/d/a8e5b2cf37e9c63c6cd9b30e47d0f45be977ec93cd31ce00苏金明《Matlab图形图像》/d/2aa4a370ef1e52037b6010336cf5555b97fbf1e5e900dc00苏金明《matlab7.0使用指南》/d/a48b5296cfb7a604e36e3201b4fcb49dcf24f34dc073c501李显洪《Matlab7.x界面设计与编译技巧/d/c4dbe1ebfec00d325a0d87ad4b85371c24cc439dd5414a01施晓红《精通GUI图形界面编程》/d/7657a037fe1ee94149ad3e3f78ff31f3d640ba9d283f0401何衍庆《控制系统分析、设计和应用——MA TLAB语言的应用/d/092ed6548c14fbb5b6db027720b06f6ae694dc9b7913af00何强《Matlab扩展编程》/d/fbb5d94f698e26526156c3bed7b32d7113b350c08557c500冈萨雷斯《数字图像处理》/d/baecf1c843361f326f7cc344d03f68550a9bef81bd6ce201 Steven T. Karris《Signals and Systems(Second Edition)》/d/c89fef493d50fead9df9840a1ca813f53d4c1e05efea4700韩利竹《Matlab电子仿真与应用(第二版)》./d/72ccd5d5083ac0e3c8dd2550ab69b540ecf94fbde7d89400 Stephen J.Chapman刑树辉《Matlab编程》/d/95dec5d8aa959317f2d753c047599eae8ba1d6a735770d01 Mohand Mokhtari著赵彦玲译《MA TLAB与SIMULINK工程应用》/d/70735fe07794def5ae718428faa16c1a70928d834c8d2101 MATLAB 7辅助信号处理技术与应用/d/1c30519cd63f1723d27e80729f98bbfc089a345c12e85602 Stephen J.Chapman《Matlab Programming For Engineers》/d/56e51a6694d03b2500b0cdbfaba7e2027e3bdf6857219b00《Matlab宝典》/d/681bb64540b50163a3d1e22cbcf7fa97d14e52c2418eec01《智能控制及其Matlab实现》/d/c5e84a25245ec0a8f9e89eb59ff25cf85c70c0102f70b300《基于MA TLABSimulink的系统仿真技术与应用》/d/d846bac3a48fcafe3a49acbd33a78b9e58c8c545bf6ce300《基于MA TLAB 7.X SIMULINK_STATEFLOW系统仿真、分析及设计》/d/d6fe321e47826be9dc39097df732e63f5ee91e0a41841101《Matlab模糊逻辑工具箱的分析与应用》/d/8088f66c62505938731165c783d385aa8f90f93784560101《Matlab与自适应神经网络模糊推理系统》/d/f8b86f03438e87a656d79d0299ac5b590d0183618a1ead00《MA TLAB数据处理与应用》/d/c7a1758b855ee3062e3ab9ea284ce30a402e3054d8f7e400《Matlab辅助控制系统设计与仿真》/d/c2655749c44ba7938df5cb26e93e479d609d8835382ca801《Matlab工具箱应用指南——信息工程篇》/d/2a482b93f8daae5c4d659cd01c77a4acd321d0db88de1401《Matlab工程数学》/d/60cb8eda0b9f3d580f3824bc2d66ed140337f97cecb6dc00 matlab初学者学习操作基本命令matlab初学者应学习操作基本命令1.有关命令行环境的一些操作:λ(1) clc擦去一页命令窗口,光标回屏幕左上角λ(2) clear从工作空间清除所有变量λ(3) clf清除图形窗口内容λ(4) who列出当前工作空间中的变量λ(5) whos列出当前工作空间中的变量及信息λ或用工具栏上的Workspace 浏览器λ(6) delete <文件名>从磁盘删除指定文件λ(7) whech <文件名>查找指定文件的路径( 9 ) clear all从工作空间清除所有变量和函数λ(10) help <命令名>查询所列命令的帮助信息λ(11) savename保存工作空间变量到文件name.matλ(12) savenamexy保存工作空间变量x y到文件name.matλ(13)loadname下载‘name’文件中的所有变量到工作空间λ(14)loadnamexy 下载‘name’文件中的变量x y到工作空间λ(15)diary name1.m保存工作空间一段文本到文件name1.m λ… diary offλ(16)type name.m在工作空间查看name.m文件内容λ(17)what列出当前目录下的m文件和mat文件↑Ctrl+p调用上一次的命令↓Ctrl+n调用下一行的命令←Ctrl+b退后一格→Ctrl+f前移一格Ctrl + ←Ctrl+r向右移一个单词Ctrl + →Ctrl+l向左移一个单词HomeCtrl+a光标移到行首EndCtrl+e光标移到行尾EscCtrl+u清除一行DelCtrl+d清除光标后字符BackspaceCtrl+h清除光标前字符Ctrl+k清除光标至行尾字Ctrl+c中断程序运行一．常用的窗口命令help 启动联机帮助文件显示what 列出当前目录下的有关文件type 列出M文件lookfor 对help信息中的关键词查找which 找出函数与文件所在的目录名demo 运行MATLAB的演示程序path 设置或查询MATLAB的路径二．有关文件及其操作的语句cd 改变当前的工作目录dir 列出当前目录的内容delete 删除文件getenv 获得环境参数unix 执行操作系统命令并返回结果diary 将MATLAB运行的命令存盘fopen 打开文件fclose 关闭文件fread 从文件中读取二进制数据fwrite 向一个文件写二进制数据fscanf 从文件读取格式化数据fprintf 将格式化数据写入文件fgetl 从文件中读行并放弃换行符fgets 从文件中读行并保持换行符ferror 查询文件的输入输出的错误信息feof 检查文件结束标志fseek 设置文件位置指针ftell 得到文件位置指针的位置prewind 反绕一个打开的文件tempname 建立临时的文件名tempdir 返回一个已存在的临时目录名三．启动与退出的命令quit,exit 退出MATLAB环境startup MATLAB自启动文件matlabrc 启动主程序四．管理变量工作空间的命令who 简要列出工作空间变量名whos 详细列出工作空间变量名load 从文件中读入变量save 列出工作空间中变量存盘clear 删除内存中的变量与函数pack 整理工作空间的内存size 查询矩阵的维数disp 显示矩阵和文本length 查询矢量的维数五．对命令窗口控制的常用命令cedit 设置命令行编辑与回调的参数clc 清除命令窗口中的显示home 将光标移动到左上角位置format 设置输出格式echo 显示文件中的MATLAB命令more 控制命令窗口的输出页面2.。

Stephen J.Chapman《MATLAB 编程(第二版) 》第一章

1.1 MATLAB 的优点
MATLAB 语言相对于传统的科技编程语言有诸多的优点。主要包括：
1.易用性
MATLAB 是种解释型语言，就像各种版本的 BASIC。和 BASIC 一样，它简单易用程序可用作便笺簿求打在命令行处表达式的值，也可执行预先写好的大型程序。在 MATLAB 集成开发环境下，程序可以方便的编写，修改和调试。这是因为这种语言极易使用，对于教育应用和快速建立新程序的原型，它是一个理想的工具。
MATLAB 是一个庞大的程序，拥有难以置信的各种丰富的函数；即使基本版本的 MATLAB 语言拥有的函数也比其他的工程编程语言要丰富的多。基本的 MATLAB 语言已经拥有了超过 1000 多个函数，而它的工具包带有更多的函数，由此扩展了它在许多专业领域的能力。本书无意将 MATLAB 的所有函数介绍给大家，而是让大家掌握编写调试和优化程序的基本功，还有一些重要函数的子集。所以从大量可利用的函数中筛选出你所需要的函数就显得尤为重要。
郑碧波翻译 Matlab 中文论坛首发 ttp://
目录
第一章 MATLAB 入门 ........................................................................................................................... 1 1.1 MATLAB 的优点 ....................................................................................................................... 1 1.易用性........................................

MATLAB英文课件

zeros()
x = zeros(2) x = 0 0 0 0 z = zeros(2,3) z = 0 0 0 0

y = zeros(1,4) y = 0 0 0
0

0 0

ones(), size(), length()
t = zeros( size(z) ) t = 0 0 0 0 0 0
MATLAB Programming for Engineers

Texts
S. J. Chapman, MATLAB Programming for Engineers(2nd edition)

Reference
张志涌等，MATLAB教程－基于6.X版本，北
航出版社许波等，MATLAB工程数学应用，清华大学出版社

If a command is followed by a semicolon (;), result of the computation is not shown on the command window
26
MATLAB Basics: Variables

Variable is a name given to a reserved location in memory
4
Introduction to MATLAB
MATrix LABoratory
Advantages of MATLAB

Ease of use Platform independence Predefined functions Plotting
22

Examine and modify search path

MATLAB简介及入门(英文PPT)

Introduc)on t o M ATLABMATLAB简介及入门Lecture O utline•The M ATLAB E nvironment (IDE)–Workspace a nd F ile s ystems (m-‐ﬁles, m at-‐ﬁle, m ex-‐ﬁle) •MATLAB B asics–Variables, O perators, B uilt-‐in f unc)ons•Flow C ontrol•PloVng•Eﬃciency: T hinking i n M ATLAB•Concluding R emarksMATLAB•Stands f or M ATrix L ABoratory•Interpreted l anguage (直译语言)•Scien)ﬁc p rogramming e nvironment•Very g ood t ool f or t he m anipula)on o f m atrices •Excellent v isualiza)on c apabili)es•Loads o f b uilt-‐in f unc)ons•Easy t o l earn a nd s imple t o u seMATLAB•How t o g et i t?–Download f rom M athworks w ebsite•Pricing a nd L icensing–MATLAB 30-‐Day F ree T rial–O^en p rovided b y y our i ns)tute–Aﬀordable s tudent l icenseCost o f s tudent l icense i n S witzerlandThe M ATLAB E nvironment (IDE)File S ystems•m-‐ﬁles–Code s cripts/User-‐deﬁned f unc)ons•mat-‐ﬁles–Data/variable s torage•mex-‐ﬁles–Callable f unc)ons b uilt f rom C/C++, o r F ortranMATLAB B asics•Variables (变量)–Type, N aming, A ssignment•Operators (操作符)–Arithme)c/Matrix/Element-‐wise/Logic o pera)ons •Built-‐in f unc)ons (内建函数)•Variable t ypes–Numeric/Logical–Character a nd s tring–Cell a nd S tructure–Table–All n umeric v ariables c an b e c onsidered a svectors/matrices/high-‐dimensional a rray–The s calar v ariables a re 1x1 m atrices w ithdouble p recision u nless s peciﬁed •Case s ensi)ve (X i s n ot e qual t o x!)•Variable n ames m ust s tart w ith a l ejerArray, M atrix•a v ector x = [1 2 5 1] x =1 2 5 1 •transpose y = x’y =1251 •a m atrix x = [12 3; 5 1 4;3 2 -1] x =1 2 35 1 43 2 -1Array, M atrix•t =1:10t =1 2 3 4 5 6 7 8 9 10 • k =2:-0.5:-1k =2 1.5 1 0.5 0 -0.5 -1•x = [1:4; 5:8]x =1 2 3 45 6 7 8Genera)ng M atrices f rom F unc)ons •zeros(M,N) M xN m atrix o f z eros •ones(M,N) M xN m atrix o f o nes•rand(M,N) M xN m atrix o f u niformly d istributed r andom n umbers o n (0,1)x = zeros(1,3)x =0 0 0x = ones(1,3)x =1 1 1 x = rand(1,3) x = 0.9501 0.2311 0.6068Matrix I ndex•The m atrix i ndices b egin f rom 1 (not 0 (as i n C )) •The m atrix i ndices m ust b e p osi)ve i ntegerA(-‐2), A (0) Error: ??? S ubscript i ndices m ust e ither b e r eal p osi)ve i ntegers o r l ogicals. A(4,2) Error: ??? I ndex e xceeds m atrix d imensions.Concatena)on o f M atrices •x = [1 2], y = [4 5], z=[ 0 0]• A = [ x y]1 2 4 5•B = [x; y]1 24 5 C = [x y ;z] Error: ??? E rror u sing ==> v ertcat C AT a rguments d imensions a re n ot c onsistent.Variables N aming T ricks•Don’t n ame y our v ariables t he s ame a s (built-‐in) f unc)ons –min, m ax, s qrt, c os, s in, t an, m ean, m edian, e tc–Otherwise y ou w ill n ot b e a ble t o u se t hese f unc)ons.•MATLAB r eserved w ords d on’t w ork e ither–i, j, e ps, n argin, e nd, p i, d ate, e tc–i, j a re r eserved a s c omplex n umbers i ni)ally•Will w ork a s c ounters i n m y e xperience s o t hey c an b e r edeﬁned a s r ealnumbers. B ut I s uggest u sing i i o r j j i nstead.Arithme)c O perators •Scalar a rithme)c o pera)onsO pera)on M ATLAB f orm–Exponen)a)on: ^ a b a^b–Mul)plica)on: * a b a*b–Right D ivision: / a / b = a/b a/b–Addi)on: + a + b a+b–Subtrac)on: -‐ a – b a-‐b•MATLAB i gnores w hite s pace b etween v ariables a nd o peratorsMatrix O pera)onsGiven A a nd B:Addi)on Subtrac)on Product TransposeElement-‐wise O pera)onsK= x ^2 ??? E rror u sing ==> m power M atrix m ust b e s quare. B=x*y ??? E rror u sing ==> m )mes I nner m atrix d imensions m ust a gree. A = [1 2 3; 5 1 4; 3 2 1] A = 1 2 3 5 1 4 3 2 -‐1y = A (3 ,:) y= 3 4 -‐1 b = x .* y b= 3 8 -‐3 c = x . / y c= 0.33 0.5 -‐3 d = x .^2 d= 1 4 9 x = A (1,:) x= 1 2 3 .* e lement-‐by-‐element m ul)plica)on ./ e lement-‐by-‐element d ivision .^ e lement-‐by-‐element p owerOrder o f O pera)ons•Parentheses•Exponen)a)on•Mul)plica)on a nd d ivision h ave e qual p recedence •Addi)on a nd s ubtrac)on h ave e qual p recedence •Evalua)on o ccurs f rom l e^ t o r ight•When i n d oubt, u se p arentheses–MATLAB w ill h elp m atch p arentheses f or y ouLogical O pera)onsExample: G et a b inaryversion o f a m atrixBuilt-‐in F unc)ons •Mathema)cal e xpressions–sqrt, l og, e xp, ...•Sta)s)cs–sum, m in, m ax, s td, ...•Element s earch–ﬁnd, i smember, u nique, ...•And m any o thers!–Always s earch t he d ocumenta)on b efore y ou i mplement y our own f unc)ons!Flow C ontrol •if•for•while•break•….•If S tatement S yntaxif (Condi)on_1)M atlab C ommands elseif (Condi)on_2)M atlab C ommandselseM atlab C ommandsendif ((a>3) & (b==5))Some Matlab Commands; endif (a<3)Some Matlab Commands; elseif (b~=5)Some Matlab Commands; endif (a<3)Some Matlab Commands; elseSome Matlab Commands; end•For l oop s yntaxfor i i=Index_ArrayM atlab C ommands endfor ii=1:100Some Matlab Commands; Endfor jj=1:3:200Some Matlab Commands; endfor m=13:-0.2:-21Some Matlab Commands; endfor k=[0.1 0.3 -13 12 7 -9.3] Some Matlab Commands; end•While L oop S yntaxwhile (condi)on)M atlab C ommands end while ((a>3) & (b==5))Some Matlab Commands; EndPloVng•Basic 2D p lot–plot, b ar, s cajer, s tem ...•Basic 3D p lot–surf, m esh, ...•Figure P roper)es–LineSpec, x label, y label, l egend, a nd s et g ca f or m ore p lot proper)eson xcomparisonDistribu)onEﬃciency: T hinking i n M ATLAB•Interpreted l anguages a re o^en s low i n e xecu)on •But, t he eﬃciency c an b e s igniﬁcantly i mproved i f you w rite y our c ode p roperly.Thinking i n M ATLAB:F ormulate y our p roblem a s m atrix o pera1ons!14x 1me f aster !!!Scajer P lotConcluding R emarks •MATLAB: A p owerful d ata a nalysis t ool •Rich b uilt-‐in f unc)ons a nd t oolbox•Very s trong d ata m anipula)on a bility •Excellent d ata v isualiza)on•Big d ata s upport: D istributed c ompu)ng p ool •Comparison w ith o ther d ata a naly)c t ools •How t o l earn M ATLAB b y y ourself ?Comparison w ith O ther D ata A naly)c T oolsSource: N YU D ata S ervicesMATLAB H elp•Product h elp w indow–Help>product h elpMATLAB O nline D ocumenta)on •Reference t o a ll t he f unc)ons•Rich e xamples a nd t utorialsMATLAB C entral•Online u ser c ommunity•Rich q ues)on/answer a nd c ode e xchanges。

MATLAB程序设计及应用第2版课件全全书教学教程完整版电子教案最全幻灯片

第1章 MATLAB入门与基本操作
1.3 MATLAB的安装启动与操作桌面简介
1.3.1 MATLAB的安装和启动
MATLAB 可以在Windows环境下直接安装。在
MATLAB安装完成后，会在Windows桌面上自动生成
MATLAB的快捷方式图标
。
1.3.1 MATLAB的安装和启动
双击图标
1.3.2 MATLAB默认窗口简介
• 指令窗（Command Window）该窗口是进行各种MATLAB操作的最主要窗口。它位于 MATLAB默认窗口的正中间。用户可以在该窗口中提示符 “fx>>”后直接键入指令，按“Enter”键后，即可运行并显示除窗口外的所有运行结果。当指令窗口提示符为 “fx>>”时，表示系统已经准备好，用户可以输入指令、函数、表达式，按“Enter”键后便可执行。
1.4 MATLAB指令窗操作入门
，就打开了如图1.1所示的MATLAB默认窗口
（Desktop）。
图1.1
1.3 MATLAB的安装启动与默认窗口简介
1.3.2 MATLAB默认窗口简介
图1.1所示的MATLAB默认窗口分为5个区域：指令窗、当前目录窗、历史指令窗、工作空间窗和Details窗。另外，在MATLAB默认窗口的上方，还嵌入了菜单栏和工具栏，如图1.1所示。它们的使用及选择方式与 Windows环境中的相同。
图1.2
第1章 MATLAB入门与基本操作
1.4 MATLAB指令窗操作入门
1.4.1 MATLAB指令窗简介
MATLAB指令窗位于MATLAB默认窗口的正中间，如图 1.1所示。如果用户希望得到脱离默认窗口的几何独立的指令窗，只要单击图1.2中的图标，并在下拉菜单中选择

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上百本matlab 的书籍下载，转载自小木虫程序软件版程序软件资源大厦/bbs/viewthread.php?tid=1452600 Matlab 的书库1。

薛定宇“高等应用数学问题的MATLAB 的求解”。

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玄光南“进化算法和优化- 理论和应用” /bbs/viewthread.php?tid=1453296 3.ppt 讲义（清华大学）。

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何衍庆“控制系统分析，设计和应用- 基于MATLAB 语言的应用”。

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钟麟“Matlab 的仿真技术与应用教程”。

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余成波“数字图像处理及Matlab 的实现”的。

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电子书-MATLAB程序设计与应用(第二版)

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数学软件MATLAB程序设计与应用第1章MATLAB系统环境1.1 MATLAB概貌1.2 MATLAB环境的准备1.3 MATLAB操作界面1.4 MATLAB帮助系统自上世纪80年代以来，出现了科学计算语言，亦称数学软件。

MATLABMathematicaMathcadMapleLINDOLINGO1.1MATLAB概貌 p3MATLAB 是 MATrix LABoratory（矩阵实验室）的缩写。

1984年由 Math Works 公司推出，现已成为国际公认的优秀的工程应用开发环境，是影响最大，流行最广的科学计算语言。

1.1.1M ATLAB的发展2.例如MATLAB7.6的建造编号是R2008a。

说明MATLAB7.6与MATLAB2008a是等同的；3.对于建造编号，正规化以后，每年出两个版本。

一般来说。

a是测试版，b是正式版。

a是前半年出，b是后半年出。

教材采用MATLAB7.0（R14，2004）实验室采用MATLAB 7.8（R2009a，2009.3，汉化）1.1.2M ATLAB的主要功能 p4◆数值计算和符号计算功能◆绘图功能◆语言体系◆MATLAB工具箱(1) 数值计算和符号计算功能MATLAB以矩阵作为数据操作的基本单位，还提供了十分丰富的数值计算函数。

MATLAB先后和著名的符号计算语言Maple与MuPAD（从MATLAB 2008b开始使用MuPAD）相结合，使得MATLAB具有符号计算功能。

(2) 绘图功能可以绘制二维和三维图形。

MATLAB提供了两个层次的绘图操作：●对图形句柄进行的低层绘图操作；●建立在低层绘图操作之上的高层绘图操作。

(3) 语言体系MATLAB具有程序结构控制、函数调用、数据结构、输入输出、面向对象等程序语言特征，而且简单易学、编程效率高。

[MATLAB图书合集].Applied.Statistics.Using.SPSS,.STATIS

Applied Statistics Using SPSS, STATISTICA, MATLAB and RJoaquim P. Marques de SáApplied StatisticsUsing SPSS, STATISTICA, MATLAB and R With195 Figures and a CD123Printed on acid-free paper 5 4 3 2 1 0SPIN: 1190894442/E d itors3100/Integra Typesettin Production:Integra Software Services Pvt.Ltd.,IndiaCover design: WMX design, Heidelbergg:by the editorsLibrary of Congress Control Number: 2007926024This work is subject to copyright.All rights are reserved,whether the whole or part of the material is concerned,speciﬁcally the rights of translation,reprinting,reuse of illustrations,recitation,broadcasting,reproduction on microﬁlm or in any other way,and storage in data banks.Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9,1965,in its current version,and permission for use must always be obtained from Springer.Violations are liable for prosecution under the German Copyright Law.Springer is a part of Springer Science+Business Media ©Springer-Verlag Berlin Heidelberg 2007The use of general descriptive names,registered names,trademarks,etc.in this publication does not imply,even in the absence of a speciﬁc statement,that such names are exempt from the relevant pro-tective laws and regulations and therefore free for general use.ISBN 978-3-540-71971-7 Springer Berlin Heidelberg New YorkProf. Dr. Joaquim P. Marques de SáUniversidade do PortoFac. Engenharia4200-465 PortoPortugale-mail: jmsa@fe.up.ptRua Dr. Roberto Frias s/nTo Wiesje and Carlos.ContentsPreface to the Second Edition xv Preface to the First Edition xvii Symbols and Abbreviations xix 1Introduction 1 1.1Deterministic Data and Random Data (1)1.2Population, Sample and Statistics (5)1.3Random Variables (8)1.4Probabilities and Distributions (10)1.4.1Discrete Variables (10)1.4.2Continuous Variables (12)1.5Beyond a Reasonable Doubt (13)1.6Statistical Significance and Other Significances (17)1.7Datasets (19)1.8Software Tools (19)1.8.1SPSS and STATISTICA (20)1.8.2MATLAB and R (22)2 Presentin g and Summarising the Data 29 2.1Preliminaries (29)2.1.1Reading in the Data (29)2.1.2Operating with the Data (34)2.2Presenting the Data (39)2.2.1Counts and Bar Graphs (40)2.2.2Frequencies and Histograms (47)2.2.3Multivariate Tables, Scatter Plots and 3D Plots (52)2.2.4Categorised Plots (56)2.3Summarising the Data (58)2.3.1Measures of Location (58)2.3.2Measures of Spread (62)2.3.3Measures of Shape (64)2.3.4 Measures of Association for Continuous Variables.....................66 2.3.5 Measures of Association for Ordinal Variables...........................69 2.3.6 Measures of Association for Nominal Variables.........................73 Exercises.................................................................................................................77 3 Estimating Data Parameters 813.1 Point Estimation and Interval Estimation..................................................81 3.2 Estimating a Mean....................................................................................85 3.3 Estimating a Proportion............................................................................92 3.4 Estimating a Variance...............................................................................95 3.5 Estimating a Variance Ratio......................................................................97 3.6 Bootstrap Estimation.................................................................................99 Exercises...............................................................................................................107 4 Parametric Tests of Hypotheses111 4.1 Hypothesis Test Procedure......................................................................111 4.2 Test Errors and Test Power.....................................................................115 4.3 Inference on One Population...................................................................121 4.3.1 Testing a Mean..........................................................................121 4.3.2 Testing a Variance.....................................................................125 4.4 Inference on Two Populations................................................................126 4.4.1 Testing a Correlation.................................................................126 4.4.2 Comparing Two Variances........................................................129 4.4.3 Comparing Two Means.............................................................132 4.5 Inference on More than Two Populations..............................................141 4.5.1 Introduction to the Analysis of Variance...................................141 4.5.2 One-Way ANOVA....................................................................143 4.5.3 Two-Way ANOVA...................................................................156 Exercises...............................................................................................................166 5 Non-Parametric Tests of Hypotheses1715.1 Inference on One Population...................................................................172 5.1.1 The Runs Test............................................................................172 5.1.2 The Binomial Test.....................................................................174 5.1.3 The Chi-Square Goodness of Fit Test.......................................179 5.1.4 The Kolmogorov-Smirnov Goodness of Fit Test......................183 5.1.5 The Lilliefors Test for Normality..............................................187 5.1.6 The Shapiro-Wilk Test for Normality.......................................187 5.2 Contingency Tables (189)5.2.1 The 2×2 Contingency Table......................................................189 5.2.2 The r x c Contingency Table.......................................................193 viii C ontentsC ontents ix5.2.3The Chi-Square Test of Independence (195)5.2.4Measures of Association Revisited (197)5.3Inference on Two Populations (200)5.3.1Tests for Two Independent Samples (201)5.3.2Tests for Two Paired Samples (205)5.4Inference on More Than Two Populations (212)5.4.1The Kruskal-Wallis Test for Independent Samples (212)5.4.2The Friedmann Test for Paired Samples (215)5.4.3The Cochran Q test (217)Exercises (218)6Statistical Classification 223 6.1Decision Regions and Functions (223)6.2Linear Discriminants (225)6.2.1Minimum Euclidian Distance Discriminant (225)6.2.2Minimum Mahalanobis Distance Discriminant (228)6.3Bayesian Classification (234)6.3.1Bayes Rule for Minimum Risk (234)6.3.2Normal Bayesian Classification (240)6.3.3Dimensionality Ratio and Error Estimation (243)6.4The ROC Curve (246)6.5Feature Selection (253)6.6Classifier Evaluation (256)6.7Tree Classifiers (259)Exercises (268)7Data Regression 271 7.1Simple Linear Regression (272)7.1.1Simple Linear Regression Model (272)7.1.2Estimating the Regression Function (273)7.1.3Inferences in Regression Analysis (279)7.1.4ANOVA Tests (285)7.2Multiple Regression (289)7.2.1General Linear Regression Model (289)7.2.2General Linear Regression in Matrix Terms (289)7.2.3Multiple Correlation (292)7.2.4Inferences on Regression Parameters (294)7.2.5ANOVA and Extra Sums of Squares (296)7.2.6Polynomial Regression and Other Models (300)7.3Building and Evaluating the Regression Model (303)7.3.1Building the Model (303)7.3.2Evaluating the Model (306)7.3.3Case Study (308)7.4Regression Through the Origin (314)xC ontents7.5Ridge Regression (316)7.6Logit and Probit Models (322)Exercises (327)8Data Structure Analysis 3298.1Principal Components (329)8.2Dimensional Reduction (337)8.3Principal Components of Correlation Matrices (339)8.4Factor Analysis (347)Exercises (350)9Survival Analysis 3539.1Survivor Function and Hazard Function (353)9.2Non-Parametric Analysis of Survival Data (354)9.2.1The Life Table Analysis (354)9.2.2The Kaplan-Meier Analysis (359)9.2.3Statistics for Non-Parametric Analysis (362)9.3Comparing Two Groups of Survival Data (364)9.4Models for Survival Data (367)9.4.1The Exponential Model (367)9.4.2The Weibull Model (369)9.4.3The Cox Regression Model (371)Exercises (373)10Directional Data 37510.1Representing Directional Data (375)10.2Descriptive Statistics (380)10.3The von Mises Distributions (383)10.4Assessing the Distribution of Directional Data (387)10.4.1Graphical Assessment of Uniformity (387)10.4.2The Rayleigh Test of Uniformity (389)10.4.3The Watson Goodness of Fit Test (392)10.4.4Assessing the von Misesness of Spherical Distributions (393)10.5Tests on von Mises Distributions (395)10.5.1One-Sample Mean Test (395)10.5.2Mean Test for Two Independent Samples (396)10.6Non-Parametric Tests (397)10.6.1The Uniform Scores Test for Circular Data (397)10.6.2The Watson Test for Spherical Data (398)10.6.3Testing Two Paired Samples (399)Exercises (400)C ontents xi Appendix A - Short Survey on Probability Theory 403 A.1Basic Notions (403)A.1.1Events and Frequencies (403)A.1.2Probability Axioms (404)A.2Conditional Probability and Independence (406)A.2.1Conditional Probability and Intersection Rule (406)A.2.2Independent Events (406)A.3Compound Experiments (408)A.4Bayes’ Theorem (409)A.5Random Variables and Distributions (410)A.5.1Definition of Random Variable (410)A.5.2Distribution and Density Functions (411)A.5.3Transformation of a Random Variable (413)A.6Expectation, Variance and Moments (414)A.6.1Definitions and Properties (414)A.6.2Moment-Generating Function (417)A.6.3Chebyshev Theorem (418)A.7The Binomial and Normal Distributions (418)A.7.1The Binomial Distribution (418)A.7.2The Laws of Large Numbers (419)A.7.3The Normal Distribution (420)A.8Multivariate Distributions (422)A.8.1Definitions (422)A.8.2Moments (425)A.8.3Conditional Densities and Independence (425)A.8.4Sums of Random Variables (427)A.8.5Central Limit Theorem (428)Appendix B - Distributions 431 B.1Discrete Distributions (431)B.1.1Bernoulli Distribution (431)B.1.2Uniform Distribution (432)B.1.3Geometric Distribution (433)B.1.4Hypergeometric Distribution (434)B.1.5Binomial Distribution (435)B.1.6Multinomial Distribution (436)B.1.7Poisson Distribution (438)B.2Continuous Distributions (439)B.2.1Uniform Distribution (439)B.2.2Normal Distribution (441)B.2.3Exponential Distribution (442)B.2.4Weibull Distribution (444)B.2.5Gamma Distribution (445)B.2.6Beta Distribution (446)B.2.7Chi-Square Distribution (448)xiiC ontentsB.2.8Student’s t Distribution (449)B.2.9 F Distribution (451)B.2.10Von Mises Distributions (452)Appendix C - Point Estimation 455C.1Definitions (455)C.2Estimation of Mean and Variance (457)Appendix D - Tables 459D.1Binomial Distribution (459)D.2Normal Distribution (465)D.3Student´s t Distribution (466)D.4Chi-Square Distribution (467)D.5Critical Values for the F Distribution (468)Appendix E - Datasets 469E.1Breast Tissue (469)E.2Car Sale (469)E.3Cells (470)E.4Clays (470)E.5Cork Stoppers (471)E.6CTG (472)E.7Culture (473)E.8Fatigue (473)E.9FHR (474)E.10FHR-Apgar (474)E.11Firms (475)E.12Flow Rate (475)E.13Foetal Weight (475)E.14Forest Fires (476)E.15Freshmen (476)E.16Heart Valve (477)E.17Infarct (478)E.18Joints (478)E.19Metal Firms (479)E.20Meteo (479)E.21Moulds (479)E.22Neonatal (480)E.23Programming (480)E.24Rocks (481)E.25Signal & Noise (481)C ontents xiii E.26Soil Pollution (482)E.27Stars (482)E.28Stock Exchange (483)E.29VCG (484)E.30Wave (484)E.31Weather (484)E.32Wines (485)Appendix F - Tools 487 F.1MATLAB Functions (487)F.2R Functions (488)F.3Tools EXCEL File (489)F.4SCSize Program (489)References 491 Index 499Preface to the Second EditionFour years have passed since the first edition of this book. During this time I have had the opportunity to apply it in classes obtaining feedback from students and inspiration for improvements. I have also benefited from many comments by users of the book. For the present second edition large parts of the book have undergone major revision, although the basic concept – concise but sufficiently rigorous mathematical treatment with emphasis on computer applications to real datasets –, has been retained.The second edition improvements are as follows:•Inclusion of R as an application tool. As a matter of fact, R is a free software product which has nowadays reached a high level of maturityand is being increasingly used by many people as a statistical analysistool.•Chapter 3 has an added section on bootstrap estimation methods, which have gained a large popularity in practical applications.• A revised explanation and treatment of tree classifiers in Chapter 6 with the inclusion of the QUEST approach.•Several improvements of Chapter 7 (regression), namely: details concerning the meaning and computation of multiple and partialcorrelation coefficients, with examples; a more thorough treatment andexemplification of the ridge regression topic; more attention dedicated tomodel evaluation.•Inclusion in the book CD of additional MATLAB functions as well as a set of R functions.•Extra examples and exercises have been added in several chapters.•The bibliography has been revised and new references added.I have also tried to improve the quality and clarity of the text as well as notation. Regarding notation I follow in this second edition the more widespread use of denoting random variables with italicised capital letters, instead of using small cursive font as in the first edition. Finally, I have also paid much attention to correcting errors, misprints and obscurities of the first edition.J.P. Marques de SáPorto, 2007Preface to the First EditionThis book is intended as a reference book for students, professionals and research workers who need to apply statistical analysis to a large variety of practical problems using STATISTICA, SPSS and MATLAB. The book chapters provide a comprehensive coverage of the main statistical analysis topics (data description, statistical inference, classification and regression, factor analysis, survival data, directional statistics) that one faces in practical problems, discussing their solutions with the mentioned software packages.The only prerequisite to use the book is an undergraduate knowledge level of mathematics. While it is expected that most readers employing the book will have already some knowledge of elementary statistics, no previous course in probability or statistics is needed in order to study and use the book. The first two chapters introduce the basic needed notions on probability and statistics. In addition, the first two Appendices provide a short survey on Probability Theory and Distributions for the reader needing further clarification on the theoretical foundations of the statistical methods described.The book is partly based on tutorial notes and materials used in data analysis disciplines taught at the Faculty of Engineering, Porto University. One of these disciplines is attended by students of a Master’s Degree course on information management. The students in this course have a variety of educational backgrounds and professional interests, which generated and brought about datasets and analysis objectives which are quite challenging concerning the methods to be applied and the interpretation of the results. The datasets used in the book examples and exercises were collected from these courses as well as from research. They are included in the book CD and cover a broad spectrum of areas: engineering, medicine, biology, psychology, economy, geology, and astronomy.Every chapter explains the relevant notions and methods concisely, and is illustrated with practical examples using real data, presented with the distinct intention of clarifying sensible practical issues. The solutions presented in the examples are obtained with one of the software packages STATISTICA, SPSS or MATLAB; therefore, the reader has the opportunity to closely follow what is being done. The book is not intended as a substitute for the STATISTICA, SPSS and MATLAB user manuals. It does, however, provide the necessary guidance for applying the methods taught without having to delve into the manuals. This includes, for each topic explained in the book, a clear indication of which STATISTICA, SPSS or MATLAB tools to be applied. These indications appear in specific “Commands” frames together with a complementary description on how to use the tools, whenever necessary. In this way, a comparative perspective of thexviii Preface to the First Editioncapabilities of those software packages is also provided, which can be quite useful for practical purposes.STATISTICA, SPSS or MATLAB do not provide specific tools for some of the statistical topics described in the book. These range from such basic issues as the choice of the optimal number of histogram bins to more advanced topics such as directional statistics. The book CD provides these tools, including a set of MATLAB functions for directional statistics.I am grateful to many people who helped me during the preparation of the book. Professor Luís Alexandre provided help in reviewing the book contents. Professor Willem van Meurs provided constructive comments on several topics. Professor Joaquim Góis contributed with many interesting discussions and suggestions, namely on the topic of data structure analysis. Dr. Carlos Felgueiras and Paulo Sousa gave valuable assistance in several software issues and in the development of some software tools included in the book CD. My gratitude also to Professor Pimenta Monteiro for his support in elucidating some software tricks during the preparation of the text files. A lot of people contributed with datasets. Their names are mentioned in Appendix E. I express my deepest thanks to all of them. Finally, I would also like to thank Alan Weed for his thorough revision of the texts and the clarification of many editing issues.J.P. Marques de SáPorto, 2003Symbols and AbbreviationsSample SetsA eventA set (of events){A1, A2,…} set constituted of events A1, A2,…A complement of {A}A U union of {A} with {B}BA I intersection of {A} with {B}BE set of all events (universe)φ emptysetFunctional Analysis∃ thereisevery∀ forto∈ belongsdoesn’t belong to∉≡ equivalentto|| || Euclidian norm (vector length)⇒ implies→ convergestoℜreal number set++∞ [ℜ [0,[a, b] closed interval between and including a and ba and b, excluding abetween]a, b] intervala and b, excluding bbetween[a, b[ intervalxx Symbols and Abbreviations]a , b [ open interval between a and b (excluding a and b )∑=n i 1 sum for index i = 1,…, n∏=n i 1 product for index i = 1,…, n ∫b aintegral from a to b k ! factorial of k , k ! = k (k −1)(k −2)...2.1()n k combinations of n elements taken k at a time | x | absolute value of xxlargest integer smaller or equal to x g X (a ) functiong of variable X evaluated at a dXdg derivative of function g with respect to X an dX g d nderivative of order n of g evaluated at a ln(x ) natural logarithm of xlog(x ) logarithm of x in base 10sgn(x ) sign of xmod(x ,y )remainder of the integer division of x by yVectors and Matricesx vector (column vector), multidimensional random vectorx' transpose vector (row vector)[x 1 x 2…x n ] row vector whose components are x 1, x 2,…,x nx ii -th component of vector x x k,ii -th component of vector x k ∆x vector x increment x'yinner (dot) product of x and y A matrixa ij i -th row, j -th column element of matrix A A' transpose of matrix AA −1 inverse of matrix ASymbols and Abbreviations xxiAmatrixof|A| determinantA (sum of the diagonal elements)tr(A) traceofI unit matrixλi eigenvalueiProbabilities and DistributionsX random variable (with value denoted by the same lower case letter, x)AeventP(A) probabilityofeventA conditioned onB having occurredP(A|B) probabilityofP(x) discrete probability of random vector xP(ωi|x)discrete conditional probability of ωi given xf(x) probability density function f evaluated at xf(x |ωi) conditional probability density function f evaluated at x given ωiX ~ f X has probability density function fX ~ F X has probability distribution function (is distributed as) FPe probability of misclassification (error)Pc probability of correct classificationdf degrees of freedomx df,αα-percentile of X distributed with df degrees of freedomb n,p binomial probability for n trials and probability p of successB n,p binomial distribution for n trials and probability p of successu uniform probability or density functionU uniform distributiong p geometric probability (Bernoulli trial with probability p)G p geometric distribution (Bernoulli trial with probability p)h N,D,n hypergeometric probability (sample of n out of N with D items)H N,D,n hypergeometric distribution (sample of n out of N with D items)pλ Poisson probability with event rate λPλ Poisson distribution with event rate λnµ,σ normal density with mean µ and standard deviation σxxii Symbols and AbbreviationsN µ,σnormal distribution with mean µ and standard deviation σ ελexponential density with spread factor λ Ελexponential distribution with spread factor λ w α,βWeibull density with parameters α, β W α,βWeibull distribution with parameters α, β γa ,pGamma density with parameters a , p Γa ,pGamma distribution with parameters a , p βp,qBeta density with parameters p , q Βp,qBeta distribution with parameters p , q 2df χ Chi-squaredensity with df degrees of freedom 2df Χ Chi-squaredistribution with df degrees of freedom t dfT df21,df df fF density with df 1, df 2 degrees of freedom 21,df df FF distribution with df 1, df 2 degrees of freedomStatisticsx ˆ estimateof x []X Εexpected value (average, mean) of X []X Vvariance of X Ε[x | y ]expected value of x given y (conditional expectation) k mcentral moment of order k µ meanvalue σ standarddeviation XY σ covarianceof X and Y ρ correlationcoefficient µ mean vectorStudent’s t density with df degrees of freedom Student’s t distribution with df degrees of freedomSymbols and Abbreviations xxiiiΣ covariance matrixx arithmetic mean v sample variances sample standard deviation x α α-quantile of X (αα=)(x F X )med(X ) median of X (same as x 0.5) S sample covariance matrixαsignificance level (1−α is the confidence level) x αα-percentile of X ε toleranceAbbreviationsFNRFalse Negative Ratio FPRFalse Positive Ratio iffif an only if i.i.d.independent and identically distributed IRQ inter-quartile rangepdfprobability density function LSE Least Square Error ML Maximum Likelihood MSE Mean Square ErrorPDFprobability distribution function RMS Root Mean Square Errorr.v. Random variableROC Receiver Operating Characteristic SSBBetween-group Sum of Squares SSEError Sum of Squares SSLFLack of Fit Sum of Squares SSPEPure Error Sum of Squares SSR Regression Sum of Squaresxxiv Symbols and AbbreviationsSST Total Sum of SquaresSSW Within-group Sum of SquaresRatioTNR TrueNegativeTPR True Positive RatioInflationFactorVIF VarianceTradenamesCorporation EXCEL MicrosoftMATLAB The MathWorks, Inc.Inc.SPSS SPSS, STATISTICA Statsoft,Inc.Corporation WINDOWS Microsoft1 Introduction1.1 Deterministic Data and Random DataOur daily experience teaches us that some data are generated in accordance toknown and precise laws, while other data seem to occur in a purely haphazard way.Data generated in accordance to known and precise laws are called deterministicgravity. When the body is released at a height h , we can calculate precisely wherethe body stands at each time t . The physical law, assuming that the fall takes placein an empty space, is expressed as:20½gt h h −=,where h 0 is the initial height and g is the Earth s gravity acceleration at the pointwhere the body falls.Figure 1.1 shows the behaviour of h with t , assuming an initial height of 15meters.t h 0.00 15.00 0.20 14.80 0.40 14.22 0.60 13.24 0.80 11.86 1.00 10.10 1.20 7.94 1.40 5.40 1.60 2.46 Figure 1.1. Body in free-fall, with height in meters and time in seconds, assumingg = 9.8 m/s 2. The h column is an example of deterministic data.data . An example of such type of data is the fall of a body subject to the Earth’s’2 1IntroductionIn the case of the body fall there is a law that allows the exact computation of one of the variables h or t (for given h0 and g) as a function of the other one. Moreover, if we repeat the body-fall experiment under identical conditions, we consistently obtain the same results, within the precision of the measurements. These are the attributes of deterministic data: the same data will be obtained, within the precision of the measurements, under repeated experiments in well-defined conditions.Imagine now that we were dealing with Stock Exchange data, such as, for instance, the daily share value throughout one year of a given company. For such data there is no known law to describe how the share value evolves along the year. Furthermore, the possibility of experiment repetition with identical results does not apply here. We are, thus, in presence of what is called random data.Classical examples of random data are:−Thermal noise generated in electrical resistances, antennae, etc.;−Brownian motion of tiny particles in a fluid;−Weather variables;−Financial variables such as Stock Exchange share values;−Gambling game outcomes (dice, cards, roulette, etc.);−Conscript height at military inspection.In none of these examples can a precise mathematical law describe the data. Also, there is no possibility of obtaining the same data in repeated experiments, performed under similar conditions. This is mainly due to the fact that several unforeseeable or immeasurable causes play a role in the generation of such data. For instance, in the case of the Brownian motion, we find that, after a certain time, the trajectories followed by several particles that have departed from exactly the same point, are completely different among them. Moreover it is found that such differences largely exceed the precision of the measurements.When dealing with a random dataset, especially if it relates to the temporal evolution of some variable, it is often convenient to consider such dataset as one realization (or one instance) of a set (or ensemble) consisting of a possibly infinite number of realizations of a generating process. This is the so-called random process (or stochastic process, from the Greek “stochastikos” = method or phenomenon composed of random parts). Thus:−The wandering voltage signal one can measure in an open electrical resistance is an instance of a thermal noise process (with an ensemble of infinitely many continuous signals);−The succession of face values when tossing n times a die is an instance of a die tossing process (with an ensemble of finitely many discrete sequences).−The trajectory of a tiny particle in a fluid is an instance of a Brownian process (with an ensemble of infinitely many continuous trajectories);。

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Voyiadjis ----Publishedby Springer----2005/bbs/viewthread.php?tid=8617541&highlight=matlabScientific Computing with MATLAB and Octave (Texts in Computational Scienceand Engineering)----- Alfio Quarteroni, Fausto Saleri, Paola Gervasio--- Springer/bbs/viewthread.php?tid=8933963&highlight=matlabEmbedded Control Systems in C C++ Using MATLAB --- Jim Ledin.chm/bbs/viewthread.php?tid=8685859&highlight=matlabMATLAB Programming Style Guildlines——by Richard Johnson/bbs/viewthread.php?tid=8926682&highlight=matlabAdaptive Filtering Primer with MATLAB --- Poularikas and Ramadan/bbs/viewthread.php?tid=8680486&highlight=matlabDevelopment and Application of the Finite Element Method based on MATLAB--- Herbert Baaser—Springer---May 2010/bbs/viewthread.php?tid=8921732&highlight=matlabPractical Matlab Basics for Engineers/bbs/viewthread.php?tid=8918039&highlight=matlabBiosignal and Biomedical Image Processing MATLAB based Applications - John L. Se/bbs/viewthread.php?tid=8672053&highlight=matlabMechanics of Composite Materials with MATLAB--George Z. Voyiadjis Peter Kattan---Springer ----2005-07-22/bbs/viewthread.php?tid=8789646&highlight=matlabMATLAB An Introduction with Applications---R.V.Dukkipati---New Age InternationalPvt Limited---2010/bbs/viewthread.php?tid=8904292&highlight=matlabMatlab Programming For Engineers》---Stephen J.Chapman/bbs/viewthread.php?tid=8787741&highlight=matlabAn Introduction to Programming and Numerical Methods in MATLAB/bbs/viewthread.php?tid=8785696&highlight=matlabApplied Numerical Methods Using MATLAB --- Yang Cao Chung and Morris/bbs/viewthread.php?tid=8683008&highlight=matlabBusiness Economics & Finance with Matlab GIS and Simulation Models---- Patrick/bbs/viewthread.php?tid=8672970&highlight=matlabMatlab Guide-----Desmond J.Higham ,Nicholos J.Higham-----siam----second edition/bbs/viewthread.php?tid=8902945&highlight=matlabMATLAB Demystified A Self-Teaching Guide---David McMahon----McGraw-Hill Professiona---1 May 2007/bbs/viewthread.php?tid=8904442&highlight=matlabLearning MATLAB----Tobin A. Driscoll (Author)----Society for Industrial and Applied Mathematics----31 Oct 2009/bbs/viewthread.php?tid=8904476&highlight=matlabCircuit Analysis I with MATLAB Computing----Steven T. Karris (Author)----Orchard Pubns---20 Mar 2009/bbs/viewthread.php?tid=8904528&highlight=matlabMATLAB Codes for Finite Element Analysis Solids and Structures----A. J. M. Ferreira(Author)----Springer---- 30 Oct 2008/bbs/viewthread.php?tid=8904515&highlight=matlabLearning Programming using MATLAB---Khalid Sayood (Author), Richard C. Dorf (Series Editor)---Morgan & Claypool Publishers----15 Dec 2006/bbs/viewthread.php?tid=8904602&highlight=matlabPractical Matlab Applications for Engineers----Misza Kalechman (Author)----CRC Press; 1 edition---September 4, 2008/bbs/viewthread.php?tid=8904436&highlight=matlabA guide to Matlab for begginers and experience user----Brian R. Hunt (Author), Ronald L. Lipsman (Author), Jonathan M. Rosenberg (Author), Kevin R. Coombes (Author), John E. Osborn (Author), Garrett J. Stuck (Author)----Cambridge University Press; 2 edition----July 10, 2006/bbs/viewthread.php?tid=8907777&highlight=matlabBusiness, Economics, and Finance with Matlab, GIS, and Simulation Models-----Patrick L. Anderson (Author) ----Chapman and Hall/CRC; 1 edition-----April 15, 2004/bbs/viewthread.php?tid=8907782&highlight=matlabCircuit Analysis II With Matlab Applications---Steven T. Karris (Author), Steven Karris (Author), Steven Karris (Author) ----Orchard Publications---- February 2004/bbs/viewthread.php?tid=8907784&highlight=matlabMATLAB Primer---Kermit Sigmon (Author), Timothy A. Davis (Author) ----Chapman and Hall/CRC;7 edition----December 29, 2004/bbs/viewthread.php?tid=8907787&highlight=matlabMATLAB Programming for Engineers----Stephen J. Chapman (Author)----CL-Engineering; 4 edition----November 8, 2007/bbs/viewthread.php?tid=8907812&highlight=matlabHall/CRC-----May 14, 2007/bbs/viewthread.php?tid=8907803&highlight=matlabA Guide to MATLAB Object-Oriented Programming----Andy H. Register (Author)---Chapman and A Guide to MATLAB Object-Oriented Programming - Andy H. Register/bbs/viewthread.php?tid=8637536&highlight=matlabElectronics and Circuit Analysis Using MATLAB - John O. Attia.pdf/bbs/viewthread.php?tid=8685855&highlight=matlabMatlab Introduction to Pattern Recognition/bbs/viewthread.php?tid=8899890&highlight=matlabChemical Process Control a First Course with Matlab - P.C. Chau/bbs/viewthread.php?tid=8683015&highlight=matlabAn Introduction to Programming and Numerical Methods in MATLAB - S.R. Otto,/bbs/viewthread.php?tid=8685849&highlight=matlabMATLAB Primer, Seventh Edition----Timothy A. Davis, Kermit Sigmon----Chapman & Hall/CRC /bbs/viewthread.php?tid=8798518&highlight=matlabAdvanced Mathematics and Mechanics Applications Using MATLAB - Howard B. Wilson/bbs/viewthread.php?tid=8670480&highlight=matlabComputational Mathematics Models Methods and Analysis with Matlab - Robert E. Wh/bbs/viewthread.php?tid=8679536&highlight=matlabExploratory Data Analysis with MATLAB (Computer Science and Data Analysis)---- Wendy L.Martinez, Angel R. Martinez--- Chapman & Hall/CRC，/bbs/viewthread.php?tid=8799889&highlight=matlabExcel Link For Use with MATLAB/bbs/viewthread.php?tid=8659416&highlight=matlabContemporary Communication Systems using Matlab - Proakis and Salehi/bbs/viewthread.php?tid=8677686&highlight=matlabDigital Signal and Image Processing Using MATLAB - Gerard Blanchet & Maurice/bbs/viewthread.php?tid=8668035&highlight=matlabMatlab Programming for Enginners 【英文影印版Stephen J.Chapman】/bbs/viewthread.php?tid=8787722&highlight=matlabMatlab Implementation of the Finite Element Method in Elasticity---J. Alberty, Kiel, C. Carstensen, Springer，2002，/bbs/viewthread.php?tid=8773386&highlight=matlabDigital Signal Processing Using Matlab V4 - Ingle and Proakis/bbs/viewthread.php?tid=8680472&highlight=matlabOptics 2ed-learning by computing, with model examples using mathcad, matlab, and maple----Karl Dieter Moller/bbs/viewthread.php?tid=8851253&highlight=matlabMathematical Methods for Mechanics: A Handbook with MATLAB Experiments---Eckart Gekeler--- Springer---- 2008-10-01/bbs/viewthread.php?tid=8694281&highlight=matlabAlgorithm Collections for Digital Signal Processing Applications using/bbs/viewthread.php?tid=8680492&highlight=matlabVibration Simulation Using MATLAB and ANSYS ---Michael R. Hatch---- Chapman & Hall/CRC--2000-09-21/bbs/viewthread.php?tid=8827007&highlight=matlabMathematical Biology: An Introduction with Maple and Matlab/bbs/viewthread.php?tid=8828072&highlight=matlabEssential Matlab for Engineer&Scientists/bbs/viewthread.php?tid=8827203&highlight=matlabEngineering and Scientific Computations Using MATLAB - Sergey E. Lyshevski/bbs/viewthread.php?tid=8821744&highlight=matlabComputational Statistics Handbook with MATLAB - Martinez & Martinez/bbs/viewthread.php?tid=8680090&highlight=matlabMatlab for Neuroscientists/bbs/viewthread.php?tid=8759164&highlight=matlabNumerical Analysis Using MATLAB® and Excel&reg--- Steven T. Karris---Orchard Publications----2007/bbs/viewthread.php?tid=8800155&highlight=matlabAn Introduction to Programming and Numerical Methods in MATLAB - S.R. Otto/bbs/viewthread.php?tid=8683007&highlight=matlab。