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扰动模型算法

扰动模型算法

扰动模型算法
扰动模型算法是一种用于处理数据隐私保护的方法。

它通过对原始数据进行一系列的扰动操作,使得输出的数据在保持一定的数据分布特征的同时,避免了对个体隐私的直接泄露。

扰动模型算法的主要原理是在原始数据中引入一定的噪声,从而对数据进行模糊化处理,使得攻击者无法从数据中直接获取个体的敏感信息。

常见的扰动模型算法包括拉普拉斯机制和指数机制。

拉普拉斯机制是一种基于指数分布的扰动模型算法。

它通过在查询结果中添加服从拉普拉斯分布的噪声,来对数据进行扰动。

具体来说,对于一个查询结果的真实值x,拉普拉斯机制会在
结果中增加一个服从均值为0,尺度参数为1/ε的拉普拉斯分
布的随机噪声。

指数机制是一种基于指数分布的扰动模型算法。

它通过对每个个体的敏感程度进行量化,并根据敏感程度决定对查询结果的扰动程度。

具体来说,指数机制会根据个体的敏感程度和查询结果的近似值,计算每个个体对查询结果的得分,然后按照得分的指数分布进行随机选择,选取一个个体作为查询结果的扰动项。

这些扰动模型算法在数据隐私保护领域得到了广泛的应用。

它们可以在保护数据隐私的同时,提供一定程度的数据可用性,使得数据可以仍然用于一些常见的数据分析任务。

量子力学英语

量子力学英语

量子力学英语
随着量子力学的发展和应用,许多新的概念和术语相继出现。

掌握量子力学英语不仅有利于学习和研究,还可以更好地沟通和交流。

以下是一些常用的量子力学英语词汇:
1. Quantum mechanics 量子力学
2. Wave function 波函数
3. Schrdinger equation 薛定谔方程
4. Uncertainty principle 不确定性原理
5. Superposition principle 叠加原理
6. Entanglement 纠缠
7. Quantum state 量子态
8. Eigenvalue 特征值
9. Eigenfunction 特征函数
10. Hamiltonian 哈密顿量
11. Operator 算符
12. Commutation relation 对易关系
13. Quantum tunneling 量子隧穿
14. Quantum entanglement 量子纠缠
15. Quantum superposition 量子叠加
以上是一些常用的量子力学英语词汇,学习量子力学英语需要不断积累和运用。

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[精彩]量子力学英语词汇

[精彩]量子力学英语词汇

1、microscopic world 微观世界2、macroscopic world 宏观世界3、quantum theory 量子[理]论4、quantum mechanics 量子力学5、wave mechanics 波动力学6、matrix mechanics 矩阵力学7、Planck constant 普朗克常数8、wave-particle duality 波粒二象性9、state 态10、state function 态函数11、state vector 态矢量12、superposition principle of state 态叠加原理13、orthogonal states 正交态14、antisymmetrical state 正交定理15、stationary state 对称态16、antisymmetrical state 反对称态17、stationary state 定态18、ground state 基态19、excited state 受激态20、binding state 束缚态21、unbound state 非束缚态22、degenerate state 简并态23、degenerate system 简并系24、non-deenerate state 非简并态25、non-degenerate system 非简并系26、de Broglie wave 德布罗意波27、wave function 波函数28、time-dependent wave function 含时波函数29、wave packet 波包30、probability 几率31、probability amplitude 几率幅32、probability density 几率密度33、quantum ensemble 量子系综34、wave equation 波动方程35、Schrodinger equation 薛定谔方程36、Potential well 势阱37、Potential barrien 势垒38、potential barrier penetration 势垒贯穿39、tunnel effect 隧道效应40、linear harmonic oscillator线性谐振子41、zero proint energy 零点能42、central field 辏力场43、Coulomb field 库仑场44、δ-function δ-函数45、operator 算符46、commuting operators 对易算符47、anticommuting operators 反对易算符48、complex conjugate operator 复共轭算符49、Hermitian conjugate operator 厄米共轭算符50、Hermitian operator 厄米算符51、momentum operator 动量算符52、energy operator 能量算符53、Hamiltonian operator 哈密顿算符54、angular momentum operator 角动量算符55、spin operator 自旋算符56、eigen value 本征值57、secular equation 久期方程58、observable 可观察量59、orthogonality 正交性60、completeness 完全性61、closure property 封闭性62、normalization 归一化63、orthonormalized functions 正交归一化函数64、quantum number 量子数65、principal quantum number 主量子数66、radial quantum number 径向量子数67、angular quantum number 角量子数68、magnetic quantum number 磁量子数69、uncertainty relation 测不准关系70、principle of complementarity 并协原理71、quantum Poisson bracket 量子泊松括号72、representation 表象73、coordinate representation 坐标表象74、momentum representation 动量表象75、energy representation 能量表象76、Schrodinger representation 薛定谔表象77、Heisenberg representation 海森伯表象78、interaction representation 相互作用表象79、occupation number representation 粒子数表象80、Dirac symbol 狄拉克符号81、ket vector 右矢量82、bra vector 左矢量83、basis vector 基矢量84、basis ket 基右矢85、basis bra 基左矢86、orthogonal kets 正交右矢87、orthogonal bras 正交左矢88、symmetrical kets 对称右矢89、antisymmetrical kets 反对称右矢90、Hilbert space 希耳伯空间91、perturbation theory 微扰理论92、stationary perturbation theory 定态微扰论93、time-dependent perturbation theory 含时微扰论94、Wentzel-Kramers-Brillouin method W. K. B.近似法95、elastic scattering 弹性散射96、inelastic scattering 非弹性散射97、scattering cross-section 散射截面98、partial wave method 分波法99、Born approximation 玻恩近似法100、centre-of-mass coordinates 质心坐标系101、laboratory coordinates 实验室坐标系102、transition 跃迁103、dipole transition 偶极子跃迁104、selection rule 选择定则105、spin 自旋106、electron spin 电子自旋107、spin quantum number 自旋量子数108、spin wave function 自旋波函数109、coupling 耦合110、vector-coupling coefficient 矢量耦合系数111、many-partic le system 多子体系112、exchange forece 交换力113、exchange energy 交换能114、Heitler-London approximation 海特勒-伦敦近似法115、Hartree-Fock equation 哈特里-福克方程116、self-consistent field 自洽场117、Thomas-Fermi equation 托马斯-费米方程118、second quantization 二次量子化119、identical particles全同粒子120、Pauli matrices 泡利矩阵121、Pauli equation 泡利方程122、Pauli’s exclusion principle泡利不相容原理123、Relativistic wave equation 相对论性波动方程124、Klein-Gordon equation 克莱因-戈登方程125、Dirac equation 狄拉克方程126、Dirac hole theory 狄拉克空穴理论127、negative energy state 负能态128、negative probability 负几率129、microscopic causality 微观因果性本征矢量eigenvector本征态eigenstate本征值eigenvalue本征值方程eigenvalue equation本征子空间eigensubspace (可以理解为本征矢空间)变分法variatinial method标量scalar算符operator表象representation表象变换transformation of representation表象理论theory of representation波函数wave function波恩近似Born approximation玻色子boson费米子fermion不确定关系uncertainty relation狄拉克方程Dirac equation狄拉克记号Dirac symbol定态stationary state定态微扰法time-independent perturbation定态薛定谔方程time-independent Schro(此处上面有两点)dinger equati on 动量表象momentum representation角动量表象angular mommentum representation占有数表象occupation number representation坐标(位置)表象position representation角动量算符angular mommentum operator角动量耦合coupling of angular mommentum对称性symmetry对易关系commutator厄米算符hermitian operator厄米多项式Hermite polynomial分量component光的发射emission of light光的吸收absorption of light受激发射excited emission自发发射spontaneous emission轨道角动量orbital angular momentum自旋角动量spin angular momentum轨道磁矩orbital magnetic moment归一化normalization哈密顿hamiltonion黑体辐射black body radiation康普顿散射Compton scattering基矢basis vector基态ground state基右矢basis ket ‘右矢’ket基左矢basis bra简并度degenerancy精细结构fine structure径向方程radial equation久期方程secular equation量子化quantization矩阵matrix模module模方square of module内积inner product逆算符inverse operator欧拉角Eular angles泡利矩阵Pauli matrix平均值expectation value (期望值)泡利不相容原理Pauli exclusion principle氢原子hydrogen atom球鞋函数spherical harmonics全同粒子identical partic les塞曼效应Zeeman effect上升下降算符raising and lowering operator 消灭算符destruction operator产生算符creation operator矢量空间vector space守恒定律conservation law守恒量conservation quantity投影projection投影算符projection operator微扰法pertubation method希尔伯特空间Hilbert space线性算符linear operator线性无关linear independence谐振子harmonic oscillator选择定则selection rule幺正变换unitary transformation幺正算符unitary operator宇称parity跃迁transition运动方程equation of motion正交归一性orthonormalization正交性orthogonality转动rotation自旋磁矩spin magnetic monent(以上是量子力学中的主要英语词汇,有些未涉及到的可以自由组合。

实变函数与泛函分析中的英文单词和短语

实变函数与泛函分析中的英文单词和短语
积分定理
integral theory
莱维单调收敛定理
Levi monotony convergence theorem
法图引理
fatou lemma
富比尼定理
Fubini theorem
有界变差函数
bounded variation function
绝对连续函数
absolutely continuous function
覆盖
cover
有限覆盖
finite cover
可数覆盖
countable cover
等价
equivalence
第三章
Chapter 3 Measure Theory
勒贝格测度Байду номын сангаас
lebesgue measure
形集合
set
形集合
set
波雷尔集合
Borel set
外侧度
exterior measure
可数可加
凸泛函
convex functional
阵列
array
弱紧性
weak compactness
弱连续性
weak continuous
弱收敛
weak convergence
弱星收敛
weak * convergence
内积
inner product
内积空间
inner product space
内点
inner point
C-空间
continuous space
紧集
compact set
完备集合
complete set
不动点
fixed point

mt4中文帮助命令中文手册

mt4中文帮助命令中文手册

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通信中的数学原理英文

通信中的数学原理英文

通信中的数学原理英文Mathematical principles in communication1. Encoding and decoding: Communication systems often involve encoding information into a format suitable for transmission and decoding it back into its original form at the receiving end. This process relies on mathematical principles to ensure the accurate transmission and recovery of information.2. Modulation: Modulation refers to the process of encoding information onto a carrier signal for efficient transmission. It involves mathematical operations such as amplitude modulation, frequency modulation, or phase modulation, which are used to represent the information in a wave form.3. Signal processing: Signal processing is a fundamental component of communication systems, and it involves mathematical operations such as convolution, Fourier transforms, and filtering. These operations are used to manipulate and analyze signals to optimize their transmission or extraction of information.4. Error detection and correction: In communication systems, errors canoccur during transmission due to noise or other impairments. Mathematical principles such as error detection codes (e.g., parity check) and error correction codes (e.g., Reed-Solomon codes) are used to detect and correct these errors, ensuring the accuracy of the transmitted data.5. Channel capacity: The channel capacity of a communication system refers to the maximum rate at which information can be reliably transmitted through a given channel. Shannon's theorem, a mathematical result derived by Claude Shannon, provides a fundamental limit on the channel capacity and allows for the optimization of communication systems.6. Data compression: Data compression techniques, such as Huffman coding or arithmetic coding, rely on mathematical principles to reduce the size of information for efficient transmission or storage. These techniques exploit patterns in the data and use mathematical algorithms to encode the information more efficiently.7. Cryptography: Cryptographic algorithms, which are used to secure the confidentiality and integrity of communication, rely on mathematical principles such as modular arithmetic, prime numbers, and discretelogarithms. These algorithms ensure the protection of sensitive information from unauthorized access or tampering.8. Information theory: Information theory is a branch of mathematics that studies the quantification, storage, and communication of information. It provides mathematical models and principles to analyze and optimize communication systems, including coding theory, data compression, and channel capacity.Overall, mathematics plays a crucial role in various aspects of communication, from encoding and modulation to error detection and correction, channel capacity, data compression, cryptography, and information theory. These mathematical principles enable efficient and reliable communication in various domains.。

Numerical atomic orbitals for linear-scaling calculations

Numerical atomic orbitals for linear-scaling calculations

Numerical atomic orbitals for linear-scaling calculationsJavier Junquera,1O´scar Paz,1Daniel Sa´nchez-Portal,2,3and Emilio Artacho41Departamento de Fı´sica de la Materia Condensada,C-III,Universidad Auto´noma,28049Madrid,Spain2Department of Physics and Materials Research Laboratory,University of Illinois,Urbana Illinois618013Departamento de Fı´sica de Materiales and DIPC,Facultad de Quı´mica,UPV/EHU,Apdo.1072E-20080San Sebastia´n,Spain 4Department of Earth Sciences,University of Cambridge,Downing Street,Cambridge CB23EQ,United Kingdom͑Received6April2001;published28November2001͒The performance of basis sets made of numerical atomic orbitals is explored in density-functional calcula-tions of solids and molecules.With the aim of optimizing basis quality while maintaining strict localization ofthe orbitals,as needed for linear-scaling calculations,several schemes have been tried.The best performanceis obtained for the basis sets generated according to a new scheme presented here,aflexibilization of previousproposals.Strict localization is maintained while ensuring the continuity of the basis-function derivative at thecutoff radius.The basis sets are tested versus converged plane-wave calculations on a significant variety ofsystems,including covalent,ionic,and metallic.Satisfactory convergence is obtained for reasonably smallbasis sizes,with a clear improvement over previous schemes.The transferability of the obtained basis sets istested in several cases and it is found to be satisfactory as well.DOI:10.1103/PhysRevB.64.235111PACS number͑s͒:71.15.Ap,71.15.MbI.INTRODUCTIONIn order to make intelligent use of the increasing power of computers for thefirst-principles simulation of ever larger and more complex systems,it is important to develop and tune linear-scaling methods,where the computational load scales only linearly with the number of atoms in the simula-tion cell.The present status of these methods and their ap-plications can be found in several reviews.1–3Essential for linear scaling is locality,and basis sets made of localized wave functions represent a very sensible basis choice.It is not only the scaling that matters,however,the prefactor be-ing also important for practical calculations.The prefactor depends significantly on two aspects of the basis:͑i͒the number of basis functions per atom,and͑ii͒the size of the localization regions of these functions.Atomic orbitals offer efficient basis sets since,even though their localization ranges are larger than those of some other methods,4the number of basis functions needed is usu-ally quite small.The price to pay for this efficiency is the lack of systematics for convergence.Unlike with plane-wave5or real-space-grid6related methods,there is no unique way of increasing the size of the basis,and the rate of convergence depends on the way the basis is enlarged.This fact poses no fundamental difficulties,it just means that some effort is needed in the preparation of unbiased basis sets,in analogy to the extra work required to prepare pseudo-potentials to describe the effect of core electrons.Maximum efficiency is achieved by choosing atomic or-bitals that allow convergence with small localization ranges and few orbitals.It is a challenge again comparable to the one faced by the pseudopotential community,where transfer-ability and softness are sought.7For atomic wave functions the optimization freedom is in the radial shape.Gaussian-type orbitals have been proposed for linear scaling,8–10con-necting with the tradition of quantum chemistry.11,12These bases are,however,quite rigid for the mentioned optimiza-tion,imposing either many Gaussians or large localization ranges.Numerical atomic orbitals͑NAO’s͒are moreflexible in this respect.Different ideas have been proposed in the litera-ture,originally within tight-binding contexts concentrating on minimal͑single␨)bases.They are obtained byfinding the eigenfunctions of the isolated atoms confined within spherical potential wells of different shapes,13–15or directly modifying the eigenfunctions of the atoms.16These schemes give strictly localized orbitals,i.e.,orbitals that are strictly zero beyond given cutoff radii r c.Afirst extension towards more complete basis sets was proposed using the excited states of the confined atoms,17but the quite delocalized char-acter of many excited states made this approach inefficient unless very stringent confinement potentials were used.18 For multiple␨,a better scheme was proposed based on the split-valence idea of quantum chemistry,11,12but adapted to strictly localized NAO’s.19In the same work,a systematic way was proposed to generate polarization orbitals suited for these basis sets.The scheme of Ref.19has proven to be quite efficient,systematic,and reasonable for a large variety of systems͑for short reviews,see Refs.19and20͒.In this work we go beyond previous methodologies be-cause of two main reasons:͑i͒It is always desirable to obtain the highest possible accuracy given the computational re-sources available,and͑ii͒it is important to know and show what is the degree of convergence attainable by NAO basis sets of reasonable sizes.We explore these issues by variationally optimizing basis sets for a variety of condensed systems.The parameters de-fining the orbitals are allowed to vary freely to minimize the total energy of these systems.This energy is then compared with that of converged plane-wave calculations for exactly the same systems,including same density functional and pseudopotentials.The optimal basis sets are then tested monitoring structural,and elastic properties of the systems.The transferability of the basis sets optimized for particu-lar systems is then checked by transferring them to other systems and testing the same energetical,structural,and elas-tic parameters.Finally,the effect of localizing the orbitalsPHYSICAL REVIEW B,VOLUME64,235111tighter than what they variationally choose is explored on a demanding system.II.METHODThe calculations presented below were all done using density-functional theory21,22͑DFT͒in its local-density23ap-proximation͑LDA͒.Core electrons were replaced by norm-conserving pseudopotentials7in their fully separable form.24 The nonlocal partial-core exchange-correlation correction25 was included for Cu to improve the description of the core-valence interactions.Periodic boundary conditions were used for all systems. Molecules were treated in a supercell scheme allowing enough empty space between molecules to make intermo-lecular interactions negligible.For solid systems,integra-tions over the Brillouin zone were replaced by converged sums over selected kជsets.26Thus far the approximations are exactly the same for the two different sets of calculations performed in this work: based on NAO’s and on plane-waves͑PW’s͒.The calcula-tions using NAO’s were performed with the SIESTA method, described elsewhere.18,27Besides the basis itself,the only additional approximation with respect to PW’s is the replace-ment of some integrals in real space by sums in afinite three-dimensional͑3D͒real-space grid,controlled by one single parameter,the energy cutoff for the grid.27This cutoff, which refers to thefineness of the grid,was converged for all systems studied here͑200Ry for all except for Si and H2,for which80and100Ry respectively,were used͒.Similarly,the PW calculations were done for converged PW cutoffs.28 Cohesive curves for the solids were obtained byfitting calculated energy values for different unit-cell volumes to cubic,quartic,and Murnaghan-like29curves,a procedure giving values to the lattice parameter,the bulk modulus and the cohesive energy of each system.The bulk moduli given by the Murnaghan and quarticfits deviate from each other by around3%,the Murnaghan values being the lowest and the ones shown in the tables.The deviations between Mur-naghan and cubicfits are of the order of7%.The other cohesive parameters do not change appreciably with thefits.The atomic-energy reference for the cohesive energy was taken from the atomic calculations within the same DFT and pseudopotentials,always converged in the basis set.They are hence the same reference for NAO’s and for PW’s,the dif-ference in cohesive energies between the two accounting for the difference in the total energy of the solid.The isolated-atom calculations included spin polarization.III.BASIS OF NUMERICAL ATOMIC ORBITALSThe starting point of the atomic orbitals that conform the basis sets used here is the solution of Kohn-Sham’s Hamil-tonian for the isolated pseudoatoms,solved in a radial grid, with the same approximations as for the solid or molecule ͑the same exchange-correlation functional and pseudopoten-tial͒.A strict localization of the basis functions is ensured either by imposing a boundary condition,by adding a con-fining͑divergent͒potential,or by multiplying the free-atom orbital by a cutting function.We describe in the following three main features of a basis set of atomic orbitals:size, range,and radial shape.A.Size:Number of orbitals per atomFollowing the nomenclature of quantum chemistry,we es-tablish a hierarchy of basis sets,from single␨to multiple␨with polarization and diffuse orbitals,covering from quick calculations of low quality to highly converged ones,as con-verged as thefinest calculations in quantum chemistry.A single␨͑also called minimal͒basis set͑SZ in the following͒has one single radial function per angular momentum chan-nel,and only for those angular momenta with substantial electronic population in the valence of the free atom.Radialflexibilization is obtained by adding a second func-tion per channel:double␨͑DZ͒.Several schemes have been proposed to generate this second function.In quantum chem-istry,the split valence11,30scheme is widely used:starting from the expansion in Gaussians of one atomic orbital,the most contracted Gaussians are used to define thefirst orbital of the double␨and the most extended ones for the second. Another proposal defines the second␨as the derivative of thefirst one with respect to occupation.31For strictly local-ized functions there was afirst proposal17of using the ex-cited states of the confined atoms,but it would work only for tight confinement.An extension of the split valence idea of quantum chemistry to strictly localized NAO’s was proposed in Ref.19and has been used quite successfully in a variety of systems.It consists of suplementing each basis orbital with a new basis function that reproduces exactly the tail of the original orbital from a given matching radius r m out-wards.The inner part goes smoothly towards the origin as r l(aϪbr2),where a and b are chosen to ensure continuity of the function and its derivative at r m.We follow this scheme in this work,which generalizes to multiple␨trivially by adding more functions generated with the same procedure.Angularflexibility is obtained by adding shells of higher angular momentum.Ways to generate these so-called polar-ization orbitals have been described in the literature,both for Gaussians11,12and for NAO’s.19In this work,however,they will be obtained variationally,as the rest,within theflexibili-ties described below.B.Range:Cutoff radii of orbitalsStrictly localized orbitals͑zero beyond a cutoff radius͒are used in order to obtain sparse Hamiltonian and overlap ma-trices for linear scaling.The traditional alternative to this is based on neglecting interactions when they fall below a tol-erance or when the atoms are beyond some scope of neigh-bors.For long ranges or low tolerances both schemes are essentially equivalent.They differ in their behavior at shorter ranges,where the strict-localization approach has the advan-tage of remaining in the Hilbert space spanned by the basis, remaining variational,and avoiding numerical instabilities no matter how short the range becomes.For the bases made of strictly localized orbitals,the prob-lem isfinding a balanced and systematic way of defining all the different cutoff radii,since both the accuracy and theJUNQUERA,PAZ,SA´NCHEZ-PORTAL,AND ARTACHO PHYSICAL REVIEW B64235111computational efficiency in the calculations depend on them.A scheme was proposed19in which all radii were defined by one single parameter,the energy shift,i.e.,the energy raise suffered by the orbital when confined.In this work,however, we step back from that systematic approach and allow the cutoff radii to vary freely in the optimization procedure͑up to a maximum value of8a.u.͒.C.ShapeWithin the pseudopotential framework it is important to keep the consistency between the pseudopotential and the form of the pseudoatomic orbitals in the core region.This is done by using as basis orbitals the solutions of the same pseudopotential in the free atom.The shape of the orbitals at larger radii depends on the cutoff radius͑see above͒and on the way the localization is enforced.Thefirst proposal13used an infinite square-well potential͑see Fig.1͒.It has been widely and successfully used for minimal bases within the ab initio tight-binding scheme of Sankey and collaborators13us-ing the FIREBALL program,but also for moreflexible bases using the methodology of SIESTA.This scheme has the disadvantage,however,of generating orbitals with a discontinuous derivative at r c as seen in Fig.1.This discontinuity is more pronounced for smaller r c’s and tends to disappear for long enough values of this cutoff.It does remain,however,appreciable for sensible values of r c for those orbitals that would be very wide in the free atom.It is surprising how small an effect such a kink produces in the total energy of condensed systems͑see below͒.It is,never-theless,a problem for forces and stresses,especially if they are calculated using a͑coarse͒finite three-dimensional grid.Another problem of this scheme is related to its defining the basis considering the free atoms.Free atoms can present extremely extended orbitals,their extension being,besides problematic,of no practical use for the calculation in con-densed systems:the electrons far away from the atom can be described by the basis functions of other atoms.Both problems can be addressed simultaneously by add-ing a soft confinement potential to the atomic Hamiltonian used to generate the basis orbitals:it smooths the kink and contracts the orbital as variationally suited.Two soft confine-ment potentials have been proposed in the literature͑Fig.1͒, both of the form V(r)ϭV o r n,one for nϭ2͑Ref.14͒and the other for nϭ6.15They present their own inconveniences,however.First,there is no radius at which the orbitals be-come strictly zero,they have to be neglected at some point. Second,these confinement potentials affect the core region spoiling its adaptation to the pseudopotential.This last problem affects a more traditional scheme as well,namely,the one based on the radial scaling of the or-bitals by suitable scale factors.In addition to very basic bonding arguments,32it is soundly based on restoring virial’s theorem forfinite bases,in the case of Coulombic potentials ͑all-electron calculations͒.33The pseudopotentials limit its applicability,allowing only for extremely small deviationsfrom unity(ϳ1%)in the scale factors obtained variationally ͑with the exception of hydrogen that can contract up to 25%͒.34An alternative scheme to avoid the kink has also beenproposed:16Instead of modifying the potential,it directlymodifies the orbitals of the atom.Following ideas of previ-ous mixed-basis schemes37the atomic orbital is multiplied by1Ϫexp͓Ϫ␣(rϪr c)2͔for rϽr c and zero otherwise.16In Ref.16it is the hard confined wave function which is thenmodified,while in Ref.37it is the free atom wave function.We follow Ref.37.This method is tested in the next section. This scheme does provide strict localization beyond r c,but introduces a different problem:for large␣and small r c a bump appears in the orbital close to r c,which becomes a discontinuity in the wave function in the limit of infinite␣͑Ref.37͒͑this is not the case in Ref.16͒.FIG.1.Shape of the3s orbital of Mg in MgO for the different confinement schemes͑a͒and corresponding potentials͑b͒.NUMERICAL ATOMIC ORBITALS FOR LINEAR-...PHYSICAL REVIEW B64235111In this work we propose a new soft confinement potential avoiding the mentioned deficiencies.It is shown in Fig.1.It isflat͑zero͒in the core region,starts off at some internal radius r i with all derivatives continuous,and diverges at r c ensuring the strict localization there.It isV͑r͒ϭV o eϪ(r cϪr i)/(rϪr i)r cϪr.͑1͒In the following the different schemes are compared,theirdefining parameters being allowed to change variationally.Finally,the shape of an orbital is also changed by theionic character of the atom.Orbitals in cations tend to shrink, and they swell in anions.Introducing a␦Q in the basis-generating free-atom calculations gives orbitals betteradapted to ionic situations in the condensed systems.IV.OPTIMIZATION PROCEDUREGiven a system and a basis size,the range and shape ofthe orbitals are defined by a set of parameters as describedabove.The parameters are described in the following.Per atomic species there is a global␦Q,an extra charge͑positive or negative͒added to the atom at the time of solving theatomic DFT problem for obtaining the basis orbitals͑see below͒.Confinement is imposed separately for each angular mo-mentum shell,with its corresponding parameters that depend on the scheme used.Hard confinement implies one param-eter per shell(r c),and our soft confinement implies three (r c,r i,and V o).One parameter(V o)is needed only in the r n-confinement schemes,14,15and two parameters in the scheme of Elsaesser et al.37(r c and the width of the cutting function͒.Finally,for each␨beyond thefirst,there is a matching radius as mentioned above.19The values of these parameters are defined variationally, according to the following procedure:͑i͒Given a set of parameters,the Kohn-Sham Hamil-tonian͑including the pseudopotential͒is solved for the iso-lated atom,in the presence of the confining potential and the extra charge␦Q.͑In the case of the scheme of Elsaesser et al.,37there is no confining potential,but an a posteriori modification of the solution wave functions.͒This is done for all the relevant l shells of all the different atomic species. The multiple zetas are built from the former using the match-ing procedure described above,19according to the r m’s within the set of parameters.This procedure gives a basis set for each set of parameter values.͑ii͒Given the basis set,a full DFT calculation is per-formed of the system for which the basis is to be optimized, normally a condensed system,solid or molecule.The Kohn-Sham total energy of this system becomes then a function of that set of parameters.Note that neither the extra charge nor the confinement potentials are added to the Kohn-Sham Hamiltonian of the system,they were just used to define the basis.The total-energy calculations are performed for given structural parameters of the studied system.We have chosen to work with experimental structures.This choice is,how-ever,of no great importance since the basis sets are supposed to be transferable enough to render any bias negligible.This is certainly the case at the DZP level,not so much for mini-mal bases.See the section on transferability below.͑iii͒The previous two steps are built in as a function into a minimization algorithm.As a robust and simple minimiza-tion method not requiring the evaluation of derivatives,we have chosen the downhill simplex method.38We have not dedicated special efforts to maximizing the efficiency of the minimization procedure since the systems used for basis op-timization typically involve a small number of atoms and the total-energy calculations are quick.The possible improve-ment in the minimization efficiency is therefore of no rel-evance to the present study.We have no argument to discard the existence of several local minima in the energy function.For the systems studied here there may be sets of parameters giving better bases than the ones we obtain.We systematically tested their robustness by restarting new simplex optimizations from the already optimized sets.More systematic searches for absolute minima,however,would require much more expensive tech-niques,which would not be justified at this point.We have thus satisfied ourselves with the ones obtained,that show good and consistent convergence characteristics.The values obtained for the parameters in the optimizations described below can be obtained from the authors.39V.RESULTSparison of different confinement schemesTable I shows the performance for MgO of the different schemes described above for constructing localized atomic orbitals.The basis sets of both magnesium and oxygen were variationally optimized for all the schemes.Mg was chosen because the3s orbital is very extended in the atom and both the kink and the confinement effects due to other orbitals are very pronounced.Results are shown for a SZ͑single s and p TABLE parison of different confinement schemes on the cohesive properties of MgO,for SZ and DZP basis sets.The gen-eralization of the different schemes to DZP is done as explained in the text.Unconfined refers to using the unconfined pseudoatomic orbitals as basis.a,B,and E c stand for lattice parameter,bulk modulus,and cohesive energy,respectively.The PW calculations were performed with identical approximations as the NAO ones except for the basis.Experimental values were taken from Ref.40.SZ DZPBasis a B E c a B E c scheme͑Å͒͑GPa͒͑eV͒͑Å͒͑GPa͒͑eV͒Unconfined 4.25119 6.49Sankey 4.1722210.89 4.1216511.82 Elsaesser 4.1622811.12 4.1216311.84 Porezag 4.1819611.17 4.0918311.83 Horsfield 4.1522111.26 4.1116811.86 This work 4.1522611.32 4.1016711.87PW 4.1016811.90 Expt. 4.2115210.3JUNQUERA,PAZ,SA´NCHEZ-PORTAL,AND ARTACHO PHYSICAL REVIEW B64235111channels for both species͒and a DZP basis͑double s and p channels plus a single d channel͒.Figure1shows the shape of the optimal3s orbital for the different schemes,and the shape of the confining potentials.The following conclusions can be drawn from the results:͑i͒Within the variational freedom offered here,the3s orbital of Mg wants to be confined to a radius of around6.5bohr, irrespective of scheme,which is extremely short for the free atom.This confinement produces a pronounced kink in the hard scheme.͑ii͒The total energy is relatively insensitive to the scheme used to generate the basis orbitals,as long as there is effective confinement.͑iii͒The basis made of uncon-fined atomic orbitals is substantially worse than any of the others.͑iv͒The pronounced kink obtained in Sankey’s hard confinement scheme is not substantially affecting the total energy as compared with the other schemes.It does perturb, however,by introducing inconvenient noise in the energy variation with volume and other external parameters,and especially in the derivatives of the energy.͑v͒The scheme proposed in this work is variationally slightly better than the other ones,but not significantly.Its main advantage is the avoidance of known problems.In the remainder of the paper, the confinement proposed in this work will be used unless otherwise specified.B.Basis convergenceTable II shows how NAO bases converge for bulk silicon.This is done by comparing different basis sizes,each of them optimized.The results are compared to converged͑50Ry͒PW results͑converged basis limit͒keeping the rest of the calculation identical.Figure2͑a͒shows the cohesion curves for this system.Even though the main point of this work is testing the convergence of NAO basis sets independently of other is-sues,we consider it interesting to gauge the relevance of the errors introduced by the basis by comparing them with other typical errors that appear in these calculations.The NAO and PW results are thus compared to all-electron LDA results49to compare basis errors with the ones produced by the pseudo-potentials.Experiment gives then reference to the error co-mitted by the underlying LDA.The comparisons above are made with respect to the converged-basis limit,for which we used PW’s up to very high cutoffs.It is important to distinguish this limit from the PW calculations at lower cutoffs,as used in many computa-tions.To illustrate this point,Fig.2͑b͒compares the energy convergence for PW’s and for NAO’s.Even though the con-vergence of NAO results is a priori not systematic with the way the basis is enlarged,the sequence of bases presented in thefigure shows a nice convergence of total energy with respect to basis size͑the number of basis functions per atom are shown in parentheses in thefigure͒:the convergence rate is similar to the one of PW’s͑DZP has three times more orbitals than SZ,and a similar factor is found for their equivalents in PW’s͒.For the particular case of Si,Fig.2 shows that the polarization orbitals(3d shell͒are very im-portant for convergence,more than the doubling of the basis. This fact is observed from the stabilization of SZP with re-spect to SZ,which is much larger than for DZ.Figure2shows that an atomic basis at the DZP level requires ten times less functions than its͑energetically͒equivalent PW basis,being Si the easiest system forPW’s.FIG.2.Convergence of NAO basis sets for bulk Si.͑a͒Cohe-sive curve for different basis sets.The lowest curve shows the PW results,filled symbols the NAO bases of this work(opt),and open symbols the NAO bases following Ref.19.Basis labels are like in Table II.͑b͒Comparison of NAO convergence with PW conver-gence.In parentheses is the number of basis functions per atom.TABLE II.Basis comparisons for bulk Si.a,B,and E c stand forlattice parameter͑inÅ͒,bulk modulus͑in GPa͒,and cohesive en-ergy͑in eV͒,respectively.SZ,DZ,and TZ stand for single␨,double␨,and triple␨.P stands for polarized,DP for doubly polar-PW results were taken from Ref.41,and the experimentalvalues from Ref.42.SZ DZ TZ SZP DZP TZP TZDP PW LAPW Expt.a 5.52 5.49 5.48 5.43 5.40 5.39 5.39 5.38 5.41 5.43B85878597979797969698.8E c 4.70 4.83 4.85 5.21 5.31 5.32 5.34 5.37 5.28 4.63NUMERICAL ATOMIC ORBITALS FOR LINEAR-...PHYSICAL REVIEW B64235111For other systems the ratio is much larger,as shown in Table III.It is important to stress that deviations smaller than the ones due to the pseudopotential or the DFT used are obtained with a relatively modest basis size as DZP.This fact is clearin Table II for Si,and in Table IV for other systems.Table IV summarizes the cohesion results for a variety of solids of different chemical kind.They are obtained with optimal DZP basis sets.It can be observed that DZP offers results in good agreement with converged-basis numbers,showing the con-vergence of properties other than the total energy.The devia-tions are similar or smaller than those introduced by LDA or by the pseudopotential.47VI.TRANSFERABILITYTo what extent do optimal bases keep their performance when transferred to different systems than the ones they were optimized for?This is an important question,since if the performance does not suffer significantly,one can hope to tabulate basis sets per species,to be used for whatever sys-tem.If the transferability is not satisfactory,a new basis set should then be obtained variationally for each system to be studied.Of course the transferability increases with basis size,since the basis has more flexibility to adapt to different environments.In this work we limit ourselves to try it on DZP bases for a few representative systems.Satisfactory transferability has been obtained when check-ing in MgO the basis set optimized for Mg bulk and O in a water molecule.Similarly,the basis for O has been tested in H 2O and O 2,and the basis for C in graphite and diamond.TABLE III.Equivalent PW cutoff (E cut )to optimal DZP basesfor different parison of number of basis functions per atom for both bases.For the molecules,a cubic unit cell of 10Åof side was used.System No.funct.DZPNo.funct.PWE cut ͑Ry ͒H 251129634O 2134544286Si1322722Diamond 1328459␣-quartz1392376TABLE IV .Basis comparisons for different solids.a ,B ,and E c stand for lattice parameter ͑in Å͒,bulk modulus ͑in GPa ͒,and co-hesive energy ͑in eV ͒,respectively.ExpLAPW Other PW PW DZP Aua 4.08a 4.05b 4.07c 4.05 4.07B 173a 198b 190c 191188E c 3.81a -- 4.19 4.03MgOa 4.21d 4.26e - 4.10 4.11B 152d 147e -168167E c 10.30d 10.40e -11.9011.87Ca 3.57a3.54f 3.54g 3.53 3.54B 442a 470f 436g 466453E c 7.37a 10.13f 8.96g 8.908.81Sia 5.43a 5.41h 5.38g 5.38 5.40B 99a 96h 94g 9697E c 4.63a 5.28h 5.34g 5.37 5.31Naa 4.23a 4.05i 3.98g 3.95 3.98B 6.9a 9.2i 8.7g 8.89.2E c 1.11a 1.44j 1.28g 1.22 1.22Cua 3.60a 3.52b 3.56g - 3.57B 138a 192b 172g -165Ec 3.50a 4.29k 4.24g - 4.37Pba 4.95a - 4.88- 4.88B 43a -54-64E c2.04a- 3.77- 3.51aC.Kittel,Ref.42.bA.Khein,D.J.Singh,and C.J.Umrigar,Ref.43.cB.D.Yu and M.Scheffler,Ref.44.dF.Finocchi,J.Goniakowski,and C.Noguera,Ref.40.eJ.Goniakowski and C.Noguera,Ref.45.fN.A.W.Holzwarth et al.,Ref.46.gM.Fuchs,M.Bockstedte,E.Pehlke,and M.Scheffler,Ref.47.hC.Filippi,D.J.Singh,and C.J.Umrigar,Ref.41.iJ.P.Perdew et al.,Ref.48.jM.Sigalas et al.,Ref.49.kP.H.T.Philipsen and E.J.Baerends,Ref.50.TABLE V .Transferability of basis sets.‘‘Transf.’’stands for the DZP basis transferred from other systems,while ‘‘Opt.’’refers to the DZP basis optimized for the particular system.For MgO the basis was transferred from bulk Mg and an H 2O molecule,for graphite the basis was transferred from diamond,and for H 2O it was taken from H 2and O 2.a ,B ,and E c stand for lattice parameter,bulk modulus,and cohesive energy,respectively.⌬E stands for the energy difference per atom between graphite and a graphene plane.E b is the binding energy of the molecule.System BasisProperties MgOa ͑Å͒B ͑GPa ͒E c ͑eV ͒Transf. 4.1315711.81Opt. 4.1016711.87PW 4.1016811.90Expt.4.2115210.30Graphitea ͑Å͒c ͑Å͒⌬E ͑meV ͒Transf. 2.456 6.5038PW a 2.457 6.7224Expt.b2.456 6.67423c H 2Od O-H ͑Å͒␪H-O-H ͑deg ͒E b ͑eV ͒Transf.0.975105.012.73Opt.0.972104.512.94PW 0.967105.113.10LAPW d 0.968103.911.05Expt.e0.958104.510.08a M.C.Schabel and J.L.Martins,Ref.51.bY .Baskin and L.Mayer,Ref.52.cL.A.Girifalco and dd,Ref.53.dP.Serena,A.Baratoff,and J.M.Soler,Ref.54.eG.Herzberg,Ref.55.JUNQUERA,PAZ,SA´NCHEZ-PORTAL,AND ARTACHO PHYSICAL REVIEW B 64235111。

代数英语

代数英语

(0,2) 插值||(0,2) interpolation0#||zero-sharp; 读作零井或零开。

0+||zero-dagger; 读作零正。

1-因子||1-factor3-流形||3-manifold; 又称“三维流形”。

AIC准则||AIC criterion, Akaike information criterionAp 权||Ap-weightA稳定性||A-stability, absolute stabilityA最优设计||A-optimal designBCH 码||BCH code, Bose-Chaudhuri-Hocquenghem codeBIC准则||BIC criterion, Bayesian modification of the AICBMOA函数||analytic function of bounded mean oscillation; 全称“有界平均振动解析函数”。

BMO鞅||BMO martingaleBSD猜想||Birch and Swinnerton-Dyer conjecture; 全称“伯奇与斯温纳顿-戴尔猜想”。

B样条||B-splineC*代数||C*-algebra; 读作“C星代数”。

C0 类函数||function of class C0; 又称“连续函数类”。

CA T准则||CAT criterion, criterion for autoregressiveCM域||CM fieldCN 群||CN-groupCW 复形的同调||homology of CW complexCW复形||CW complexCW复形的同伦群||homotopy group of CW complexesCW剖分||CW decompositionCn 类函数||function of class Cn; 又称“n次连续可微函数类”。

Cp统计量||Cp-statisticC。

弱无穷小算子算法

弱无穷小算子算法

弱无穷小算子算法简介弱无穷小算子算法(Weak Infinitesimal Operator Algorithm)是一种用于解决非线性优化问题的数值计算方法。

它通过将非线性问题转化为一系列线性问题的求解,从而有效地降低了计算的复杂度。

背景在实际问题中,我们经常需要求解非线性优化问题,即最小化或最大化一个非线性目标函数的值。

这类问题通常无法直接应用传统的数值优化方法进行求解,因为非线性函数具有复杂的数学形式,难以找到全局最优解。

弱无穷小算子算法应运而生,为我们提供了一种有效且高效的求解非线性优化问题的方法。

基本思想弱无穷小算子算法基于泰勒展开和牛顿迭代方法,并结合了弱收敛理论。

它将原始的非线性优化问题转化为一系列线性子问题来求解。

具体来说,该算法通过引入一个弱无穷小量(infinitesimal)来逐步逼近原始目标函数,并使用牛顿迭代方法更新当前点的估计值,直到满足收敛准则为止。

算法步骤1.初始化:选择初始点和收敛准则的阈值,设定迭代次数上限。

2.迭代更新:根据泰勒展开,将原始目标函数在当前点进行二阶近似,并引入弱无穷小量。

3.线性子问题求解:将二阶近似后的目标函数转化为一个线性子问题,通过求解线性子问题得到下一步的迭代点。

4.收敛判断:计算当前点与上一步迭代点之间的差异,并与收敛准则进行比较。

如果满足收敛准则,则停止迭代;否则返回第2步继续迭代。

5.输出结果:返回最终收敛的点作为最优解。

算法特点•高效性:弱无穷小算子算法通过将非线性优化问题转化为一系列线性子问题来求解,大大降低了计算复杂度,提高了计算效率。

•全局收敛性:该算法基于牛顿迭代方法,具有全局收敛性。

在合理的初始点选择和适当的参数设定下,可以得到全局最优解。

•鲁棒性:弱无穷小算子算法对于非线性函数形式的要求相对较低,适用于各种类型的非线性优化问题。

•可扩展性:该算法可以与其他优化算法相结合,例如遗传算法、模拟退火等,形成一种混合优化方法,以解决更加复杂的问题。

三维稀疏卷积原理

三维稀疏卷积原理

三维稀疏卷积原理
三维稀疏卷积的原理主要是建立在哈希表的基础上,用于保存特定位置的计算结果。

在输入数据中,只有少量的点(即非零元素或激活输入点)具有实际的值,而大部分点都是零值。

这种稀疏性使得稀疏卷积成为一种有效的计算方式。

在稀疏卷积中,卷积核的定义与传统卷积相同,但输出定义有所不同。

稀疏卷积有两种主要的输出定义方式:regular output definition 和submanifold output definition。

在regular output definition 中,只要卷积核覆盖到一个输入点,就会计算输出点。

而在submanifold output definition中,输出点的计算则更加严格,只有满足特定条件的输入点才会被用于计算输出。

三维稀疏卷积在处理大规模三维数据时具有显著的优势。

由于输入数据的稀疏性,稀疏卷积能够大大减少不必要的计算,从而显著提高计算效率。

此外,稀疏卷积还能够保留输入数据中的关键信息,使得在处理大规模数据时能够保持较高的准确性。

总的来说,三维稀疏卷积是一种针对稀疏数据的高效计算方法,通过利用输入数据的稀疏性来减少计算量,提高计算效率,同时保持较高的准确性。

NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS Numer. Linear Algebra Appl. 2003 000 Prepared us

NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS Numer. Linear Algebra Appl. 2003 000 Prepared us
gence theory is presented for a substructuring preconditioner based on constrained energy minimization concepts. The substructure spaces consist of local functions with zero values of the constraints, while the coarse space consists of minimal energy functions with the constraint values continuous across substructure interfaces. In applications, the constraints include values at corners and optionally averages on edges and faces. The preconditioner is reformulated as an Additive Schwarz method and analyzed by building on existing results for Balancing Domain Decomposition. The main result is a bound on the condition number based on inequalities involving the matrices of the preconditioner. Estimates of the form C (1+log 2 (H/h)) are obtained under the standard assumptions of substructuring theory. Computational results demonstrating the performance of method are included. Copyright c 2003 John Wiley & Sons, Ltd. key words: Iterative substructuring, FETI, Balancing Domain Decomposition, NeumannNeumann, Additive Schwarz, non-overlapping domain decomposition

信息论与编码理论中的英文单词和短语

信息论与编码理论中的英文单词和短语

信息论与编码理论Theories of Information
and Coding
第一章介绍
Chapter 1 Introduction
第二章信息理论Chapter 2 Information Theory
信息论与编码理论中的英文单词和短语
第三章 离散无记忆信
道和容量成本方程
Chapter 3 Discrete Memory less Channels and their Capacity -Cost Equations
第四章 离散无记忆信
源和扭曲率方程
Chapter 4 Discrete Memoryless Sources and their Rate -Distortion Equations
第五章 高斯信道和信

Chapter 5 Gaussian Channel and Source
第六章 信源-信道编码
理论
Chapter 6 Source -Channel Coding Theory
第七章 第一部分访问
先进标题
Chapter 7 Survey of Advanced Topics for Part One
第八章线性码Chapter 8 Linear codes
第九章循环码Chapter 9 Cyclic Codes
第十章 香农码和相关
的码
Chapter 10 Shannon Codes and Related Codes
第十一章 卷积码
Chapter 11 Convolution Codes
第十二章变量长度源编

Chapter 12 Variable-length Source Coding。

卷积 维特比译码 c语言

卷积 维特比译码 c语言

卷积维特比译码c语言卷积码和维特比(Viterbi)译码是两种在通信系统中常用的编码和解码技术。

卷积码是一种线性分组码,它通过将输入信息序列与一组预定的约束条件进行卷积运算来生成编码序列。

而维特比译码是一种高效的解码算法,用于从接收到的信号中恢复出原始的编码序列。

下面是一个简单的C语言示例,演示了如何实现卷积编码和维特比译码。

请注意,这只是一个基本的示例,实际的实现可能会更复杂,并且需要更多的错误处理和优化。

c复制代码:#include <stdio.h>#include <stdlib.h>#define N 4#define K 2#define G 2// 卷积编码函数void convolutional_encode(int input[K], int code[N]) {int i, j;for (i = 0; i < N; i++) {code[i] = 0;}for (i = 0; i < K; i++) {code[i] = input[i];}for (i = K; i < N; i++) {code[i] = (code[i - 1] ^ code[i - 2]) & G;}}// 维特比译码函数void viterbi_decode(int received[N], int output[K]) {int branch_metric[N][2];int path_metric[N];int max_metric, new_max_metric;int max_path, new_max_path;int i, j, k;for (i = 0; i < N; i++) {path_metric[i] = abs(received[i] - 0); // 初始化路径度量branch_metric[i][0] = abs(received[i] - 0); // 初始化分支度量branch_metric[i][1] = abs(received[i] - G); // 初始化分支}for (i = 0; i < N; i++) {output[i] = 0; // 初始化输出序列}for (i = 0; i < N; i++) {if (branch_metric[i][0] > branch_metric[i][1]) {output[i] = 0; // 选择分支0作为当前的最优路径path_metric[i] = branch_metric[i][0]; // 更新路径度量} else {output[i] = 1; // 选择分支1作为当前的最优路径path_metric[i] = branch_metric[i][1]; // 更新路径度量}if (path_metric[i] > max_metric) {max_metric = path_metric[i]; // 记录最大路径度量max_path = i; // 记录最大路径度量对应的路径值} else if (path_metric[i] == max_metric) { // 如果当前路径度量与最大路径度量相等,则选择路径值较小的路径作为最优路径new_max_metric = path_metric[i]; // 记录新的最大路径度量new_max_path = i; // 记录新的最大路径度量对应的路} else if (path_metric[i] < max_metric && path_metric[i] > new_max_metric) { // 如果当前路径度量比新记录的最大路径度量要小,但是比之前的最大路径度量要大,则更新新的最大路径度量和对应的路径值new_max_metric = path_metric[i]; // 更新新的最大路径度量new_max_path = i; // 更新新的最大路径度量对应的路径值} else if (path_metric[i] < max_metric && path_metric[i] < new_max_metric) { // 如果当前路径度量比新记录的最大路径度量要小,但是比之前的最大路径度量要小,则更新新的最大路径度量和对应的路径值,同时更新最优路径为新记录的最大路径对应的路径值和对应的分支值new_max_metric = new_max_metric; // 更新新的最大路径度量不变new_max_path = i; // 更新新的最大路径度量对应的路径值为当前路径。

卷积码的图解表示

卷积码的图解表示

001 000
000 000
000 000

电子信息工程学院
11
信息论
1 卷积码的解析表示
生成矩阵
101 011 G
000 001 101 011
001 000 000 001 101

000 000 000 000 001 011 001 000 电子信息工程学院 000 000 001 000 000
c0
t
c1
t
c2
t
输出码字
电子信息工程学院
5
信息论
1 卷积码的解析表示
几个基本概念

码字长度 n 编码约束长度N 编码记忆长度L 码率(编码效率) k/n 卷积码记为(n,k,L)
电子信息工程学院
6
信息论
1 卷积码的解析表示
生成矩阵和 生成多项式矩阵
输入M
m0

t
m0

t 1
电子信息工程学院
8
信息论
1 卷积码的解析表示
基本生成矩阵
0 1 2 g G G G 00 111 011 001 000 000

生成矩阵
G
111 011 001 000 000 000 111 011 001 000 000 000 111 011 001 电子信息工程学院
信息论
卷积码的基本概念

卷积码的提出与发展 1954年,埃里斯(Elias)提出卷积码的概念,它是完全不 同于线性分组码的一个码类。 1961年,提出卷积码的序列译码方法。 1963年,梅西(Massey)提出了卷积码的代数译码方法— 门限译码。 1967年,维特比(Vitebi)提出了卷积码的最大似然译码 方法,称为维特比算法。直到现在,仍是应用最为广泛的 1 译码算法。 电子信息工程学院

乘法的英文

乘法的英文

乘法的英文我们从小学开始就学习乘法,很多人都对九九乘法表记忆犹新。

那么你知道乘法的英文是什么吗?下面是店铺为你整理的乘法的英文,希望大家喜欢!乘法的英文multiplicationmultiplication signmultiplicativemultiplication常见用法n.增加,增殖,倍增; [数]乘法,乘法运算;1. Increasing gravity is known to speed up the multiplication of cells.我们知道不断增加的引力会加速细胞的分裂。

2. We had multiplication tables drilled into us at school.以前我们上学得反复背诵乘法表.3. The teacher hammers away at the multiplication tables.老师反复地念诵乘法表.4. The teacher hammered away at the multiplication tables.老师一再朗读乘法表.5. There will be simple tests in addition, subtraction, multiplication and division.会有对加、减、乘、除运算的简单测试。

6. Our teacher used to drum our multiplication tables into us.我们老师过去老是让我们反覆背诵乘法表.7. In other words, F respects addition, multiplication and identity element.换言之, F保持加, 乘法和单位元.8. Multiplication of permutations , unlike multiplication of numbers, is not always commutative.置换的乘法不同于数的乘法, 它并不一定满足交换律.9. The multiplication of numbers has made our club building too small.会员的增加使得我们的俱乐部拥挤不堪.10. Further multiplication of the virus produced papules on the skin.病毒的进一步增殖使皮肤发生丘疹.multiplicative 例句1. A multiplication sign indicates the multiplicative relationship between two numbers.乘号表示两个数字相乘的关系.2. A multiplicative constitutive model of hyperelastoplasticity is adopted to simulate large deformation.为模拟更大的变形采用了极分解的乘法超弹塑性本构模型.3. The multiplicative complexity of the two - dimensional discrete Hartley trans ( ? ) m of size 2~ n ×2~ n, where (? )本文研究了长度为2~n×2 ~n ( n为正整数) 二维离散哈特莱( Hartley ) 变换的乘法复杂性.4. The common image noise is the main additive noise, multiplicative noise and quantization noise.图像的常见噪声主要有加性噪声、乘性噪声和量化噪声等.5. ACCURATE ALGORITHM FOR NUMERICAL SIMULATION OF NONLINEAR STOCHASTIC PROCESS DRIVED BY MULTIPLICATIVE COLORED NOISE.倍增色噪声激励的非线性随机过程的精确数值模拟.6. An implementation for computing multiplicative inverses in Galois fields GF ( 2 m ) is presented.在扩展欧几里得算法的基础上提出了有限域乘法逆元的计算方法.7. A multiplicative constitutive model of the hyperelastic - plasticity is used to simulate the large deformations.采用乘法分解超弹塑性本构模型,以便模拟更大的变形.8. We study the semirings additive reduct are semilattices and multiplicative reduct are rectangular groups.研究了加法半群为半格、乘法半群为矩形群的半环.。

数学专业词汇及翻译

数学专业词汇及翻译

一、字母顺序表 (1)二、常用的数学英语表述 (7)三、代数英语(高端) (13)一、字母顺序表1、数学专业词汇Aabsolute value 绝对值 accept 接受 acceptable region 接受域additivity 可加性 adjusted 调整的 alternative hypothesis 对立假设analysis 分析 analysis of covariance 协方差分析 analysis of variance 方差分析 arithmetic mean 算术平均值 association 相关性 assumption 假设 assumption checking 假设检验availability 有效度average 均值Bbalanced 平衡的 band 带宽 bar chart 条形图beta-distribution 贝塔分布 between groups 组间的 bias 偏倚 binomial distribution 二项分布 binomial test 二项检验Ccalculate 计算 case 个案 category 类别 center of gravity 重心 central tendency 中心趋势 chi-square distribution 卡方分布 chi-square test 卡方检验 classify 分类cluster analysis 聚类分析 coefficient 系数 coefficient of correlation 相关系数collinearity 共线性 column 列 compare 比较 comparison 对照 components 构成,分量compound 复合的 confidence interval 置信区间 consistency 一致性 constant 常数continuous variable 连续变量 control charts 控制图 correlation 相关 covariance 协方差 covariance matrix 协方差矩阵 critical point 临界点critical value 临界值crosstab 列联表cubic 三次的,立方的 cubic term 三次项 cumulative distribution function 累加分布函数 curve estimation 曲线估计Ddata 数据default 默认的definition 定义deleted residual 剔除残差density function 密度函数dependent variable 因变量description 描述design of experiment 试验设计 deviations 差异 df.(degree of freedom) 自由度 diagnostic 诊断dimension 维discrete variable 离散变量discriminant function 判别函数discriminatory analysis 判别分析distance 距离distribution 分布D-optimal design D-优化设计Eeaqual 相等 effects of interaction 交互效应 efficiency 有效性eigenvalue 特征值equal size 等含量equation 方程error 误差estimate 估计estimation of parameters 参数估计estimations 估计量evaluate 衡量exact value 精确值expectation 期望expected value 期望值exponential 指数的exponential distributon 指数分布 extreme value 极值F factor 因素,因子 factor analysis 因子分析 factor score 因子得分 factorial designs 析因设计factorial experiment 析因试验fit 拟合fitted line 拟合线fitted value 拟合值 fixed model 固定模型 fixed variable 固定变量 fractional factorial design 部分析因设计 frequency 频数 F-test F检验 full factorial design 完全析因设计function 函数Ggamma distribution 伽玛分布 geometric mean 几何均值 group 组Hharmomic mean 调和均值 heterogeneity 不齐性histogram 直方图 homogeneity 齐性homogeneity of variance 方差齐性 hypothesis 假设 hypothesis test 假设检验Iindependence 独立 independent variable 自变量independent-samples 独立样本 index 指数 index of correlation 相关指数 interaction 交互作用 interclass correlation 组内相关 interval estimate 区间估计 intraclass correlation 组间相关 inverse 倒数的iterate 迭代Kkernal 核 Kolmogorov-Smirnov test柯尔莫哥洛夫-斯米诺夫检验 kurtosis 峰度Llarge sample problem 大样本问题 layer 层least-significant difference 最小显著差数 least-square estimation 最小二乘估计 least-square method 最小二乘法 level 水平 level of significance 显著性水平 leverage value 中心化杠杆值 life 寿命 life test 寿命试验 likelihood function 似然函数 likelihood ratio test 似然比检验linear 线性的 linear estimator 线性估计linear model 线性模型 linear regression 线性回归linear relation 线性关系linear term 线性项logarithmic 对数的logarithms 对数 logistic 逻辑的 lost function 损失函数Mmain effect 主效应 matrix 矩阵 maximum 最大值 maximum likelihood estimation 极大似然估计 mean squared deviation(MSD) 均方差 mean sum of square 均方和 measure 衡量 media 中位数 M-estimator M估计minimum 最小值 missing values 缺失值 mixed model 混合模型 mode 众数model 模型Monte Carle method 蒙特卡罗法 moving average 移动平均值multicollinearity 多元共线性multiple comparison 多重比较 multiple correlation 多重相关multiple correlation coefficient 复相关系数multiple correlation coefficient 多元相关系数 multiple regression analysis 多元回归分析multiple regression equation 多元回归方程 multiple response 多响应 multivariate analysis 多元分析Nnegative relationship 负相关 nonadditively 不可加性 nonlinear 非线性 nonlinear regression 非线性回归 noparametric tests 非参数检验 normal distribution 正态分布null hypothesis 零假设 number of cases 个案数Oone-sample 单样本 one-tailed test 单侧检验 one-way ANOVA 单向方差分析 one-way classification 单向分类 optimal 优化的optimum allocation 最优配制 order 排序order statistics 次序统计量 origin 原点orthogonal 正交的 outliers 异常值Ppaired observations 成对观测数据paired-sample 成对样本parameter 参数parameter estimation 参数估计 partial correlation 偏相关partial correlation coefficient 偏相关系数 partial regression coefficient 偏回归系数 percent 百分数percentiles 百分位数 pie chart 饼图 point estimate 点估计 poisson distribution 泊松分布polynomial curve 多项式曲线polynomial regression 多项式回归polynomials 多项式positive relationship 正相关 power 幂P-P plot P-P概率图predict 预测predicted value 预测值prediction intervals 预测区间principal component analysis 主成分分析 proability 概率 probability density function 概率密度函数 probit analysis 概率分析 proportion 比例Qqadratic 二次的 Q-Q plot Q-Q概率图 quadratic term 二次项 quality control 质量控制 quantitative 数量的,度量的 quartiles 四分位数Rrandom 随机的 random number 随机数 random number 随机数 random sampling 随机取样random seed 随机数种子 random variable 随机变量 randomization 随机化 range 极差rank 秩 rank correlation 秩相关 rank statistic 秩统计量 regression analysis 回归分析regression coefficient 回归系数regression line 回归线reject 拒绝rejection region 拒绝域 relationship 关系 reliability 可*性 repeated 重复的report 报告,报表 residual 残差 residual sum of squares 剩余平方和 response 响应risk function 风险函数 robustness 稳健性 root mean square 标准差 row 行 run 游程run test 游程检验Sample 样本 sample size 样本容量 sample space 样本空间 sampling 取样 sampling inspection 抽样检验 scatter chart 散点图 S-curve S形曲线 separately 单独地 sets 集合sign test 符号检验significance 显著性significance level 显著性水平significance testing 显著性检验 significant 显著的,有效的 significant digits 有效数字 skewed distribution 偏态分布 skewness 偏度 small sample problem 小样本问题 smooth 平滑 sort 排序 soruces of variation 方差来源 space 空间 spread 扩展square 平方 standard deviation 标准离差 standard error of mean 均值的标准误差standardization 标准化 standardize 标准化 statistic 统计量 statistical quality control 统计质量控制 std. residual 标准残差 stepwise regression analysis 逐步回归 stimulus 刺激 strong assumption 强假设 stud. deleted residual 学生化剔除残差stud. residual 学生化残差 subsamples 次级样本 sufficient statistic 充分统计量sum 和 sum of squares 平方和 summary 概括,综述Ttable 表t-distribution t分布test 检验test criterion 检验判据test for linearity 线性检验 test of goodness of fit 拟合优度检验 test of homogeneity 齐性检验 test of independence 独立性检验 test rules 检验法则 test statistics 检验统计量 testing function 检验函数 time series 时间序列 tolerance limits 容许限total 总共,和 transformation 转换 treatment 处理 trimmed mean 截尾均值 true value 真值 t-test t检验 two-tailed test 双侧检验Uunbalanced 不平衡的 unbiased estimation 无偏估计 unbiasedness 无偏性 uniform distribution 均匀分布Vvalue of estimator 估计值 variable 变量 variance 方差 variance components 方差分量 variance ratio 方差比 various 不同的 vector 向量Wweight 加权,权重 weighted average 加权平均值 within groups 组内的ZZ score Z分数2. 最优化方法词汇英汉对照表Aactive constraint 活动约束 active set method 活动集法 analytic gradient 解析梯度approximate 近似 arbitrary 强制性的 argument 变量 attainment factor 达到因子Bbandwidth 带宽 be equivalent to 等价于 best-fit 最佳拟合 bound 边界Ccoefficient 系数 complex-value 复数值 component 分量 constant 常数 constrained 有约束的constraint 约束constraint function 约束函数continuous 连续的converge 收敛 cubic polynomial interpolation method三次多项式插值法 curve-fitting 曲线拟合Ddata-fitting 数据拟合 default 默认的,默认的 define 定义 diagonal 对角的 direct search method 直接搜索法 direction of search 搜索方向 discontinuous 不连续Eeigenvalue 特征值 empty matrix 空矩阵 equality 等式 exceeded 溢出的Ffeasible 可行的 feasible solution 可行解 finite-difference 有限差分 first-order 一阶GGauss-Newton method 高斯-牛顿法 goal attainment problem 目标达到问题 gradient 梯度 gradient method 梯度法Hhandle 句柄 Hessian matrix 海色矩阵Independent variables 独立变量inequality 不等式infeasibility 不可行性infeasible 不可行的initial feasible solution 初始可行解initialize 初始化inverse 逆 invoke 激活 iteration 迭代 iteration 迭代JJacobian 雅可比矩阵LLagrange multiplier 拉格朗日乘子 large-scale 大型的 least square 最小二乘 least squares sense 最小二乘意义上的 Levenberg-Marquardt method 列文伯格-马夸尔特法line search 一维搜索 linear 线性的 linear equality constraints 线性等式约束linear programming problem 线性规划问题 local solution 局部解M medium-scale 中型的 minimize 最小化 mixed quadratic and cubic polynomialinterpolation and extrapolation method 混合二次、三次多项式内插、外插法multiobjective 多目标的Nnonlinear 非线性的 norm 范数Oobjective function 目标函数 observed data 测量数据 optimization routine 优化过程optimize 优化 optimizer 求解器 over-determined system 超定系统Pparameter 参数 partial derivatives 偏导数 polynomial interpolation method 多项式插值法Qquadratic 二次的 quadratic interpolation method 二次内插法 quadratic programming 二次规划Rreal-value 实数值 residuals 残差 robust 稳健的 robustness 稳健性,鲁棒性S scalar 标量 semi-infinitely problem 半无限问题 Sequential Quadratic Programming method 序列二次规划法 simplex search method 单纯形法 solution 解 sparse matrix 稀疏矩阵 sparsity pattern 稀疏模式 sparsity structure 稀疏结构 starting point 初始点 step length 步长 subspace trust region method 子空间置信域法 sum-of-squares 平方和 symmetric matrix 对称矩阵Ttermination message 终止信息 termination tolerance 终止容限 the exit condition 退出条件 the method of steepest descent 最速下降法 transpose 转置Uunconstrained 无约束的 under-determined system 负定系统Vvariable 变量 vector 矢量Wweighting matrix 加权矩阵3 样条词汇英汉对照表Aapproximation 逼近 array 数组 a spline in b-form/b-spline b样条 a spline of polynomial piece /ppform spline 分段多项式样条Bbivariate spline function 二元样条函数 break/breaks 断点Ccoefficient/coefficients 系数cubic interpolation 三次插值/三次内插cubic polynomial 三次多项式 cubic smoothing spline 三次平滑样条 cubic spline 三次样条cubic spline interpolation 三次样条插值/三次样条内插 curve 曲线Ddegree of freedom 自由度 dimension 维数Eend conditions 约束条件 input argument 输入参数 interpolation 插值/内插 interval取值区间Kknot/knots 节点Lleast-squares approximation 最小二乘拟合Mmultiplicity 重次 multivariate function 多元函数Ooptional argument 可选参数 order 阶次 output argument 输出参数P point/points 数据点Rrational spline 有理样条 rounding error 舍入误差(相对误差)Sscalar 标量 sequence 数列(数组) spline 样条 spline approximation 样条逼近/样条拟合spline function 样条函数 spline curve 样条曲线 spline interpolation 样条插值/样条内插 spline surface 样条曲面 smoothing spline 平滑样条Ttolerance 允许精度Uunivariate function 一元函数Vvector 向量Wweight/weights 权重4 偏微分方程数值解词汇英汉对照表Aabsolute error 绝对误差 absolute tolerance 绝对容限 adaptive mesh 适应性网格Bboundary condition 边界条件Ccontour plot 等值线图 converge 收敛 coordinate 坐标系Ddecomposed 分解的 decomposed geometry matrix 分解几何矩阵 diagonal matrix 对角矩阵 Dirichlet boundary conditions Dirichlet边界条件Eeigenvalue 特征值 elliptic 椭圆形的 error estimate 误差估计 exact solution 精确解Ggeneralized Neumann boundary condition 推广的Neumann边界条件 geometry 几何形状geometry description matrix 几何描述矩阵 geometry matrix 几何矩阵 graphical user interface(GUI)图形用户界面Hhyperbolic 双曲线的Iinitial mesh 初始网格Jjiggle 微调LLagrange multipliers 拉格朗日乘子Laplace equation 拉普拉斯方程linear interpolation 线性插值 loop 循环Mmachine precision 机器精度 mixed boundary condition 混合边界条件NNeuman boundary condition Neuman边界条件 node point 节点 nonlinear solver 非线性求解器 normal vector 法向量PParabolic 抛物线型的 partial differential equation 偏微分方程 plane strain 平面应变 plane stress 平面应力 Poisson's equation 泊松方程 polygon 多边形 positive definite 正定Qquality 质量Rrefined triangular mesh 加密的三角形网格 relative tolerance 相对容限 relative tolerance 相对容限 residual 残差 residual norm 残差范数Ssingular 奇异的二、常用的数学英语表述1.Logic∃there exist∀for allp⇒q p implies q / if p, then qp⇔q p if and only if q /p is equivalent to q / p and q are equivalent2.Setsx∈A x belongs to A / x is an element (or a member) of Ax∉A x does not belong to A / x is not an element (or a member) of AA⊂B A is contained in B / A is a subset of BA⊃B A contains B / B is a subset of AA∩B A cap B / A meet B / A intersection BA∪B A cup B / A join B / A union BA\B A minus B / the diference between A and BA×B A cross B / the cartesian product of A and B3. Real numbersx+1 x plus onex-1 x minus onex±1 x plus or minus onexy xy / x multiplied by y(x - y)(x + y) x minus y, x plus yx y x over y= the equals signx = 5 x equals 5 / x is equal to 5x≠5x (is) not equal to 5x≡y x is equivalent to (or identical with) yx ≡ y x is not equivalent to (or identical with) yx > y x is greater than yx≥y x is greater than or equal to yx < y x is less than yx≤y x is less than or equal to y0 < x < 1 zero is less than x is less than 10≤x≤1zero is less than or equal to x is less than or equal to 1| x | mod x / modulus xx 2 x squared / x (raised) to the power 2x 3 x cubedx 4 x to the fourth / x to the power fourx n x to the nth / x to the power nx −n x to the (power) minus nx (square) root x / the square root of xx 3 cube root (of) xx 4 fourth root (of) xx n nth root (of) x( x+y ) 2 x plus y all squared( x y ) 2 x over y all squaredn! n factorialx ^ x hatx ¯ x barx ˜x tildex i xi / x subscript i / x suffix i / x sub i∑ i=1 n a i the sum from i equals one to n a i / the sum as i runs from 1 to n of the a i4. Linear algebra‖ x ‖the norm (or modulus) of xOA →OA / vector OAOA ¯ OA / the length of the segment OAA T A transpose / the transpose of AA −1 A inverse / the inverse of A5. Functionsf( x ) fx / f of x / the function f of xf:S→T a function f from S to Tx→y x maps to y / x is sent (or mapped) to yf'( x ) f prime x / f dash x / the (first) derivative of f with respect to xf''( x ) f double-prime x / f double-dash x / the second derivative of f with r espect to xf'''( x ) triple-prime x / f triple-dash x / the third derivative of f with respect to xf (4) ( x ) f four x / the fourth derivative of f with respect to x∂f ∂ x 1the partial (derivative) of f with respect to x1∂ 2 f ∂ x 1 2the second partial (derivative) of f with respect to x1∫ 0 ∞the integral from zero to infinitylim⁡x→0 the limit as x approaches zerolim⁡x→0 + the limit as x approaches zero from abovelim⁡x→0 −the limit as x approaches zero from belowlog e y log y to the base e / log to the base e of y / natural log (of) yln⁡y log y to the base e / log to the base e of y / natural log (of) y一般词汇数学mathematics, maths(BrE), math(AmE)公理axiom定理theorem计算calculation运算operation证明prove假设hypothesis, hypotheses(pl.)命题proposition算术arithmetic加plus(prep.), add(v.), addition(n.)被加数augend, summand加数addend和sum减minus(prep.), subtract(v.), subtraction(n.)被减数minuend减数subtrahend差remainder乘times(prep.), multiply(v.), multiplication(n.)被乘数multiplicand, faciend乘数multiplicator积product除divided by(prep.), divide(v.), division(n.)被除数dividend除数divisor商quotient等于equals, is equal to, is equivalent to 大于is greater than小于is lesser than大于等于is equal or greater than小于等于is equal or lesser than运算符operator数字digit数number自然数natural number整数integer小数decimal小数点decimal point分数fraction分子numerator分母denominator比ratio正positive负negative零null, zero, nought, nil十进制decimal system二进制binary system十六进制hexadecimal system权weight, significance进位carry截尾truncation四舍五入round下舍入round down上舍入round up有效数字significant digit无效数字insignificant digit代数algebra公式formula, formulae(pl.)单项式monomial多项式polynomial, multinomial系数coefficient未知数unknown, x-factor, y-factor, z-factor 等式,方程式equation一次方程simple equation二次方程quadratic equation三次方程cubic equation四次方程quartic equation不等式inequation阶乘factorial对数logarithm指数,幂exponent乘方power二次方,平方square三次方,立方cube四次方the power of four, the fourth power n次方the power of n, the nth power开方evolution, extraction二次方根,平方根square root三次方根,立方根cube root四次方根the root of four, the fourth root n次方根the root of n, the nth root集合aggregate元素element空集void子集subset交集intersection并集union补集complement映射mapping函数function定义域domain, field of definition值域range常量constant变量variable单调性monotonicity奇偶性parity周期性periodicity图象image数列,级数series微积分calculus微分differential导数derivative极限limit无穷大infinite(a.) infinity(n.)无穷小infinitesimal积分integral定积分definite integral不定积分indefinite integral有理数rational number无理数irrational number实数real number虚数imaginary number复数complex number矩阵matrix行列式determinant几何geometry点point线line面plane体solid线段segment射线radial平行parallel相交intersect角angle角度degree弧度radian锐角acute angle直角right angle钝角obtuse angle平角straight angle周角perigon底base边side高height三角形triangle锐角三角形acute triangle直角三角形right triangle直角边leg斜边hypotenuse勾股定理Pythagorean theorem钝角三角形obtuse triangle不等边三角形scalene triangle等腰三角形isosceles triangle等边三角形equilateral triangle四边形quadrilateral平行四边形parallelogram矩形rectangle长length宽width附:在一个分数里,分子或分母或两者均含有分数。

时间不相容的随机控制问题和弱形式的正倒向随机微分方程

时间不相容的随机控制问题和弱形式的正倒向随机微分方程
在金融数学、控制系统等领域,时间不相容问题指的是 随机控制策略与期望收益之间存在矛盾,无法同时达到 最优的问题。该问题具有广泛的应用背景,如投资组合 管理、风险管理等。解决该问题对于提高策略的有效性 和稳定性具有重要意义。
要点二
弱形式的正倒向随机微分方程( Weak FBSDE)
FBSDE是一种描述金融市场动态的随机微分方程,其中 正向过程描述资产价格的变化,而倒向过程描述风险溢 价的变化。Weak FBSDE是FBSDE的一种弱形式,适用 于更广泛的市场环境。研究Weak FBSDE的解的性质对 于理解和预测市场动态具有重要意义。
缺乏有效的数值方法
对于这类问题的数值求解方法的研究还比较薄弱,还没有形成一套有效的数值求解方法,这使得许多问题无法通过数值模 拟或计算得到解决。
研究趋势与展望
01
发展新的理论框架
未来的研究将致力于构建一个系统性 的理论框架,以便更好地理解和解决 时间不相容的随机控制问题和弱形式 的正倒向随机微分方程。
时间不相容性是指随机控制问题的 未来状态和过去状态之间存在依赖 关系。在正倒向随机微分方程中, 这种依赖关系表现为未来状态依赖 于过去状态和未来的随机干扰。
VS
正倒向随机微分方程是一种描述时 间不相容的随机控制问题的数学模 型,其中过去状态和未来状态之间 存在双向的依赖关系。
弱形式正倒向随机微分方程对时间不相容性的描述
时间不相容的随机控制问题 和弱形式的正倒向随机微分
方程
2023-10-29
contents
目录
• 引言 • 时间不相容随机控制问题 • 弱形式的正倒向随机微分方程 • 时间不相容性与弱形式正倒向随机微分方
程关系 • 时间不相容性与弱形式正倒向随机微分方

信息论基础与编码21

信息论基础与编码21

• ③重复第二步的计算、比较和判决过程。若输入接收序 列长为 (l+L)k,其中,后 L 段是人为加入的全0段,则译 码一直进行到 (l+L) 个时刻为止。
• 若进入某个状态的部分路径中,有两条的部分路径值相
等,则可任选其一作为幸存路径。
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维特比译码的应用
• 维特比译码技术在目前已作为一个标准技术在宇航和 卫星通信系统中获得广泛应用。
5
4
S3
5
R= 10
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01
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第八步
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对本例而言,按上述算法进行到第八步后,四条路 径的前面分支都合并在一起。所以,只要译码深度足够, 就可达到较低的错误概率。依此类推,对接收序列中的 诸码组进行译码。 • 维特比译码的一次运算:
– 计算每个输入分支的度量值(分支距离、累加距 离);
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维特比译码工作原理
• 译码器不是在篱笆图上一次就计算和比较 2Lk 条路径,而是接收一段,就计算、比较一段, 从而在每个状态时,选择进入该状态的最可能 的分支。
• 维特比译码的基本思想:将接收序列 R 与篱 笆图上的路径逐分支地比较,然后留下与 R 距离最小的路径,称为幸存路径,而去掉其余 可能的路径,并将这些幸存路径逐分支地延长 并存储起来。
最大似然译码/最小距离译码
• 译码器接收到 R 序列后,按最大似然法则力图 寻找编码器在网格图上原来走过的路径,也就 是寻找具有最大度量的路径;
• 因此,译码器必须寻找与 R 有最小距离的路径, 即计算和寻找 min[d(R, Cj)]。
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维特比译码的基本原理
• 在起始的第0个到第2个时刻内,编码器根据输入的信息元不 同从S0状态向四个可能的状态之一行进; • 本例假定信息序列长为L=5个信息组,最后 m =2个信息组是 全0,所以在篱笆图上的最后两个时刻向 S0 状态返回; • 篱笆图上各连续分支组成了可能的路径,它们代表了各种可 能的码序列; • 由于可能的输入信息序列有 2kL=25=32 个,可能的路径有32条; • 每个分支上的数字表示输出的子码。
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Keywords: dominating set, connected domination number, distance, isometric set, convex set.
Mathematics SuC12, 05C69, 05C99.
1. INTRODUCTION Let G = (V, E) be a connected undirected graph. The neighbourhood of a vertex v ∈ V in G is the set NG(v) of all vertices adjacent to v in G. For a set X ⊆ V , the open neighbourhood NG(X) is defined to be v∈X NG(v) and the closed neighbourhood NG[X] = NG(X) ∪ X. Let X be a set of vertices and let u ∈ X. We say that a vertex v is a private neighbour of u, with respect to X, if NG[v] ∩ X = {u}.
Theorem 1. For any k, r ∈ N where r ≥ 3, there exists a graph G such that γc(G) = γwcon(G) = r and γcon(G) − γc(G) = γcon(G) − γwcon(G) = k.
Proof. Assume first that k ∈ N , r = 3. Let H be a complete bipartite graph isomorphic to Kk+1,2 and let x be a vertex
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Magdalena Lemańska
in G if no two vertices of D are adjacent. A set is independent dominating if it is independent and dominating. The domination number of G, denoted γ(G), is the minimum cardinality of a dominating set in G, while the connected domination number γc(G) is the minimum cardinality of a connected dominating set in G. The distance dG(u, v) between two vertices u and v in a connected graph G is the length of the shortest (u − v) path in G. A (u − v) path of length dG(u, v) is called (u − v)geodesic. The diameter diam G of a connected graph G is maxu,v∈V (G) dG(u, v). A set X ⊆ V is called weakly convex (or isometric [4]) in G if for every two vertices a, b ∈ X exists (a − b)-geodesic whose vertices belong to X. A set X is convex in G if vertices from all (a − b)-geodesic belong to X for every two vertices a, b ∈ X. A set X ⊆ V is a weakly convex dominating set if X is weakly convex and dominating. Further, X is a convex dominating set if it is convex and dominating. The weakly convex domination number γwcon(G) of a graph G is the minimum cardinality of a weakly convex dominating set, while the convex domination number γcon(G) of a graph G is the minimum cardinality of a convex dominating set. Convex and weakly convex domination numbers were first introduced by Jerzy Topp, Gdansk University of Technology, 2002. The union G = G1 ∪ G2 has V (G) = V (G1) ∪ V (G2) and E(G) = E(G1) ∪ E(G2) and the join G = G1 + G2 has V (G) = V (G1) ∪ V (G2) and E(G) = E(G1) ∪ E(G2) ∪ {uv : u ∈ V (G1), v ∈ V (G2)}. The corona G = H ◦ K1 is the graph G constructed from a copy of H, where for each vertex v ∈ V (H), a new vertex v′ and a pendant edge vv′ are added.
x=u
y=v
Fig. 1
In such a graph G, the minimum connected dominating set consists of all supports. This set is also weakly convex, so γc(G) = γwcon(G) = r. It is obvious that the minimum convex dominating set consists of all non-end-vertices, so γcon(G) = n − r = k + r. Thus γcon(G) − γc(G) = γcon(G) − γwcon(G) = k.
2. RELATIONS BETWEEN γwcon, γcon AND THE OTHER DOMINATION PARAMETRES
Since every convex dominating set is weakly convex dominating set and every weakly convex dominating set is connected dominating set, we have following inequality chain.
The degree degG(v) of a vertex v is the number of edges incident to v, degG(v) = = |NG(v)|. If degG(v) = r for every vertex v ∈ V in G, then G is said to be regular of degree r, or simply r-regular. A 3-regular graph is also called a cubic graph. A 2-regular graph of order n is a cycle and is denoted by Cn. If degG(v) = 1, then v is called an end-vertex or a leaf of G. A vertex which is a neighbour of an end-vertex let us call a support. A vertex x ∈ V is called a universal vertex (or a dominating vertex ) if deg(x) = |V (G)| − 1. A set D ⊂ V is a dominating set of G if NG[D] = V . A dominating set D is a perfect dominating set if |NG(v) ∩ D| = 1 for each v ∈ V − D. Further, D is a connected dominating set if D is dominating and the subgraph D induced by D, is connected. A set D ⊂ V is independent
of minimum degree in H. Let y and z be two neighbours of x. Let G be a graph
Weakly convex and convex domination numbers
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which results if we identify y with one support of P6 (a path with six vertices) and z with another support of P6. The set {x, y, z} is a minimum connected dominating set and a weakly convex set in G, so we have γc(G) = γwcon(G) = 3. It is easy to observe that V (H) is a minimum convex dominating set of G and therefore γcon(G) = k + 3. Thus γcon(G) − γc(G) = γcon(G) − γwcon(G) = k.
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