Binary Codes

合集下载

gcc语言编译原理_CompilingBinaryFilesUsingACompiler

Making plain binaryﬁles using a C compiler(i386+)Cornelis FrankApril10,2000I wrote this article because there isn’t much information on the Internet concerning this topic and I needed this for the EduOS project.No liability is assumed for incidental or consequential damages in connection with or arising out of use of the information or programs contained herein.So if you blow up your computer because of my bad“English”that’s your problem not mine. 1Which tools do you need?An i386PC or higher.A Linux distribution like Red Hat or Slackware.GNU GCC compiler.This C compiler usually comes with Linux.To check if you’re having GCC type the following at the prompt:gcc--versionThis should give an output like:2.7.2.3The number probably will not match the above one,but that doesn’t really matter.The binutils for Linux.NASM Version0.97or higher.The Netwide Assembler,NASM,is an80x86assembler designed for portability and modularity.It supports a range of objectﬁle formats,including Linux‘a.out’and ELF,NetBSD/FreeBSD,COFF,Microsoft16-bit OBJ and Win32.It will also output plain binaryﬁles.Its syntax is designed to be simple and easy to understand, similar to Intel’s but less complex.It supports Pentium,P6and MMX opcodes,and has macro capability.Normally you don’t have NASM on your system.Download it from:/pub/Linux/devel/lang/assemblers/A text editor like pico or emacs.1See also:Intel Architecture Software Developer’s Manual,V olume1:Basic Architecture,1.4.1.Bit and Byte Order2See also:Intel Architecture Software Developer’s Manual,V olume1:Basic Architecture,4.2.2.Stack Alignment00000000211111111121000000002010Wherein x stands for a number represented in base x.Notice also that negative numbers are characterized by having the high bit on.Of course you don’t have to do the conversion to a negative version of a certain number yourself.The IA-32architecture has a speciﬁc instruction for this,called NEG.Table1shows us the two’s complement representation of a char.The advantageRangeunsigned128255011273See also:Intel Architecture Software Developer’s Manual,V olume1:Basic Architecture,6.3.2.1.Type Conver-sion Instructions4See also:Intel Architecture Software Developer’s Manual,V olume1:Basic Architecture,3.3.Memory Organi-zation5See also:Intel Architecture Software Developer’s Manual,V olume3:System Programming Guide,Chapter3: Protected-mode memory management6Source:A Book on C,fourth edition,A.10.Variable Argumentsstart ,the variable v is the last argument that is declared in the header to yourvariable argument function deﬁnition.This variable cannot be of storage class register ,and it cannot be an array type or a type such as char that is widened by automatic conversions.The macro va arg accesses the next argument in the list.The macro varoundedstart will let theargumentebp ebp + 0x4ebp + 0x8Figure 2:The arguments on the IA-32stackpointer ap point to the variable after the given (ﬁrst)variable v .This macro doesn’t return anything (indicated by the leading (void)).The macro vaend will reset the argument pointer ap without returning anything.23。

数据依赖的多索引哈希算法_马艳萍_姬光荣_邹海林_谢洪涛

第42卷第4期 JOURNAL OF XIDIAN UNIVERSITY V ol.42 No.4 ______________________________收稿日期：网络出版时间：基金项目：国家自然科学基金资助项目(61170161，61303171，61271406)作者简介：马艳萍(1975-), 女, 博士研究生, E-mail ：myp74920@网络出版地址： doi ：10.3969/j.issn.1001-2400.2015.04.026数据依赖的多索引哈希算法马艳萍2,1，姬光荣1，邹海林2，谢洪涛3(1. 中国海洋大学信息科学与工程学院，山东青岛 266100；2．鲁东大学信息与电气工程学院，山东烟台 2640253．中国科学院信息工程研究所信息内容安全技术国家工程实验室，北京，100093)摘要：多索引哈希是目前使用最广泛的针对二进制码的索引算法. 由于多索引哈希基于数据集中的二进制码呈均匀分布这一假设，不能有效处理非均匀分布的数据集. 针对这一问题，提出数据依赖的多索引哈希算法. 首先把二进制码划分为多个连续不重合的子串，并通过计算二进制码每位之间的相关性为每一个子串学习得到自适应投影向量. 在为每个子串建立哈希表时，使用投影向量对子串进行投影从而得到哈希表中的下标. 采用自适应投影的方法可以使得哈希表中的元素接近于均匀分布，进而提升查询速度. 此外，提出一个基于熵的分布度量方法，以评价哈希表中数据元素的分布情况. 在大规模数据集上的实验表明，与多索引哈希算法相比数据依赖的多索引哈希算法可以使查询速度提升36.9%–87.4%.关键词：最近邻查询；二进制码；索引；多索引哈希中图分类号：TP183 文献标识码：A 文章编号：1001-2400(2015)04-0177-07Data-oriented multi-index HashingMA Y anping 1,2, JI Guangrong 1, ZOU Hailin 2, XIE Hongtao 3(1School of Information Science and Engineering, Ocean University of China, Qingdao, 2661002Scholol of Information and Electrical Engineering, Ludong University, Y antai, 2640253Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093)Abstract: Multi-index hashing (MIH) is the state-of-the-art method for indexing binary codes. However, MIH isbased on the dataset codes uniform distribution assumption, and will lose efficiency in dealing with non-uniformlydistributed codes. In this paper, we propose a data-oriented multi-index hashing method. W e first compute thecorrelations between bits and learn adaptive projection vector for each binary substring. Then, instead of usingsubstrings as direct indices into hash tables, we project them with corresponding projection vectors to generate newindices. With adaptive projection, the indices in each hash table are near uniformly distributed. Besides, we putforward an entropy based measurement to evaluate the distribution of data items in each hash table. Experimentsbe improved by 36.9%–87.4%.Key Words: nearest neighbor search; binary codes; indexing; multi-index Hashing在大规模的数据集中进行最近邻查询是图像检索[1][14]、计算机视觉[2][15]、目标检测[3]等领域的一个基础工作. 由于二进制码特征计算快速、节省存储空间、特征之间的匹配操作仅需要几个机器指令就能完成，目前越来越多的研究采用二进制码特征来描述视觉内容[4][5][6]. 在一个具有百万规模的二进制码数据集中查找一个查询的最近邻可以在不到一秒的时间内完成[7].虽然二进制码之间的海明距离可以快速计算，但是线性查询只能处理小规模的数据集. 因为计算机处2014-11-05 16:16/kcms/doi/10.3969/j.issn.1001-2400.2015.04.026.html理器的计算能力有限而数据集的规模是无限的，随着数据集的增长（数以百亿）线性查询将变得很慢. 为了提高大规模数据环境下二进制码的最近邻查询性能，Salakhutdinov等人提出了二进制哈希方法[4][8]. 该方法在建索引时，直接使用二进制码作为哈希表的下标（存储地址）. 在查询时，通过不断增加查询半径即可返回与查询相似的最近邻. 但是随着查询半径的增加，该方法需要比对的待检测数据呈指数级的增长. 当二进制码的位数大于32维时，即使采用一个很小的查询半径二进制哈希在理论上需要比对的数据规模可能比整个数据集的容量还要大[7]. 在这种情况下，二进制哈希比线性查询的速度还要慢. 针对这一问题，W eiss 等人提出了多索引哈希算法[8]. 多索引哈希算法在建立索引时将二进制码划分为多个连续不重合的子串，并为每个子串建立一个哈希表. 在查询时，按照同样的方式把待查询二进制码划分为多个子串，然后在相应的哈希表中进行查找以返回候选结果. 最后，根据候选结果和查询之间的海明距离对候选结果排序从而得到最近邻. 对每一个子串，其所需的查询半径与整个二进制码相比大大减小. 因此，多索引哈希算法极大地降低了需要比对的待检测数据量，从而提高查找最近邻的速度. 由于多索引哈希算法基于数据集中的二进制码呈均匀分布这一假设[7]，不能有效处理非均匀分布的数据集. 在多媒体检索中，数据集的分布往往都是非均匀的[1], 因此多索引哈希算法在处理这些数据集时，查询速度受到一定的影响和限制[7][11].针对多索引哈希算法不能有效应对非均匀分布的数据集这一问题，作者提出数据依赖的多索引哈希算法，算法框架图如图1所示. 首先把二进制码划分为多个连续不重合的子串. 然后构建一个训练数据集并计算二进制码每位之间的相关性，为每一个子串学习得到自适应投影向量. 在为每个子串建立哈希表时，使用投影向量对子串进行投影从而得到哈希表中的下标. 采用自适应投影的方法可以使得哈希表中的元素接近于均匀分布，进而提升查询速度. 此外，作者还提出一个基于熵的分布度量方法，以评价哈希表中数据元素的分布情况. 在大规模数据集上的实验表明，与多索引哈希算法相比数据依赖的多索引哈希算法可以使查询速度提升36.9%–87.4%.图1 数据依赖的多索引哈希算法示意图.1算法描述本节首先简要介绍多索引哈希算法[7]，然后详细描述数据依赖的多索引哈希算法. 除此以外，作者还提出了一个基于熵[1]的数据分布度量方法.1.1多索引哈希算法虽然计算二进制码之间的海明距离只需要几个异或操作，但是线性查找不能有效地应对大规模的数据集. 因此，Norouzi结合二进制码和哈希表提出了二进制哈希方法[4][7][8]. 二进制哈希把海明空间下的最近邻查询问题转化为R近邻问题：第4期马艳萍等：数据依赖的多索引哈希算法 179 , 1,2,...,,i i H q p r i N p D −≤=∈ , (1)其中q 是查询向量，D 是数据集，N 是数据集中元素的个数，H •代表海明距离. 通过不断增加查询半径r ，二进制哈希算法可以返回查询向量q 的R 近邻. 为了提高查询速度，二进制哈希算法建立一个哈希表，并直接使用二进制码作为数据元素在哈希表中的下标. 这样，R 近邻问题就可以通过不断增加查询半径r 得到解决. 此时，需要比对的待检测数据量为：0ri l i num C ==∑, (2)其中l 是二进制码的维度. 当二进制码的维数很长时，即使采用一个很小的查询半径r ，二进制哈希在理论上需要比对的数据规模可能比整个数据集的容量还要大[7]. 比如当l=256, r =5，1010num ≈. 而在很多应用中，二进制码的长度都大于256维并且查询半径一般都大于10，以满足检索精度的需求[6]. 在这种情况下，二进制哈希比线性查找还要慢.针对上述问题，Norouzi 提出多索引哈希算法[7]. 该算法在建立索引时将长度为 l 维的二进制码划分为m 个连续不重合的子串，每个子串的长度为l ⎡⎤⎢⎥或者l m ⎢⎥⎣⎦；然后为每个子串建立一个哈希表. 在查询时，按照同样的方式把待查询二进制码划分为 m 个子串，然后在相应的哈希表中进行查找以返回候选结果. 最后根据候选结果和查询之间的海明距离对候选结果排序并得到最近邻. 多索引哈希算法[7]的理论基础是：当两个二进制码 q 和 p 有r 位不相同时，那么至少它们的一个子串最多有r m ⎢⎥⎣⎦位不同：1 .. k kH k m s t q p r m ∃≤≤−≤⎢⎥⎣⎦, (3)其中k q 是q 的第k 个子串. 通过这种方式，多索引哈希算法可以极大地降低了需要比对的待检测数据量. 比如当l=256, r =5 , m=2, 需要比对的数据量为21280*i i m C =∑=16,512, 远远小于1010. 因此多索引哈希算法在索引长二进制码时具有明显的优势. 但是多索引哈希算法基于数据集中的二进制码呈均匀分布这一假设[7]，不能有效处理非均匀分布的数据集. 在多媒体检索中，数据集的分布往往都是非均匀的[1][11]. 因此多索引哈希算法具有两个缺点：z 如果待检测区间分布的数据元素比较密集，那么在对候选结果计算距离并排序时需要很多额外的时间开销，从而增加计算量.z 如果待检测区间分布的数据元素比较稀疏，那么候选结果太少. 为了保证足够多的候选结果，不得不增加查询半径r , 这样增加了索引查询时间.1.2 多索引哈希算法通过1.1节的分析可以看出，多索引哈希算法的时间性能依赖于数据集的分布. 为了得到最优的时间性能，需要使哈希表中元素下标的分布尽可能呈均匀分布. 因此，作者在多索引哈希算法的基础上提出数据依赖的多索引哈希算法，算法框架如图1所示. 通过构建一个训练数据集并计算二进制码每位之间的相关性，为每一个子串学习得到自适应投影向量. 在为每个子串建立哈希表时，使用投影向量对子串进行投影从而得到哈希表中的下标. 采用自适应投影的方法可以使得哈希表中的元素下标接近于均匀分布，进而提升查询速度.数据集的非均匀分布是由于二进制码的各个位之间具有相关性造成的[7][11]. 主成分分析（PrincipalComponent Analysis ，PCA ）[10] 是一种用来揭示复杂数据潜在的简单结构的数据分析技术. PCA 通过计算新的一组基对原有数据进行线性变换，变换后的数据尽量揭示原有数据之间的关系，且具有线性不相关性.PCA 的优点是简单有效且无参数设置，因此在计算机视觉领域应用广泛. 基于这一理论基础，作者采用PCA 来生成投影向量，以得到分布均匀的投影数据. 从而在尽量保留原始数据近邻关系的前提下，将索引均衡化. 数据依赖的多索引哈希算法执行步骤如下：a. 构建一个训练数据集1[,,,]i n T x x x ="用于PCA 训练. i x 是一个l 维二进制码，用一个列向量表示.为了算法的普适性，训练集和用于建立索引的基准数据集没有重合.b. 计算训练集T 的均值向量μ和协方差矩阵S ：西安电子科技大学学报（自然科学版）第42卷 180 11n i i x n μ==∑,,1()()n T i j i j S x x μμ==−−∑. (4) c. 对于每一个子串，获取其对应的协方差矩阵'S .'S 是S 的一个子矩阵. 然后对矩阵'S 进行特征值分解，得到对应最大特征值的特征向量V .向量V 即为该子串的自适应投影向量.d. 在建立索引和查询时，使用投影向量对子串进行投影从而得到哈希表中的下标. 假设某一子串为1[,,...,]i d p p p p =，那么新的下标值为：1**2dd i i i i indice p V −==∑ (5)由于投影向量包含数据集的分布信息，并去除数据之间的相关性，生成的哈希表中元素下标接近于均匀分布，从而提升查询速度.1.3 数据分布度量在信息论中，熵是对不确定性的测量. 信息熵越高，能传输的信息越多，信息熵越低，意味着传输的信息越少. 为了度量哈希表中数据元素的分布情况，作者提出一个基于熵的分布度量函数. 对于一个哈希表h , 假设数据集的大小为N , 哈希表h 有num_b 个哈希桶，第i 个哈希桶有()n i 个数据元素. 那么把某一个二进制串分配到第i 个哈希桶的概率估算为()()p i n i N =. 哈希表h 的分布熵定义为：_1()(()*log(()))num bi E h p i p i ==−∑. (6)直观上，如果哈希表的分布熵值比较大，那么其中的数据元素更接近于均匀分布. 通过这一度量公式，可以近似地量化和对比哈希表中数据元素的分布情况.2 实验本节通过大量实验验证本文算法的有效性. 在实验的第1 部分, 首先介绍实验所用的数据集和评测方法；第2部分分析训练集的大小对算法性能的影响；第3部分验证算法的有效性和扩展性.2.1 实验数据集和评测方法实验在著名的ANN_SIFT1B 数据集[12]上开展. 该数据集的元素是128维的SIFT 描述子[13], 其中包含910的基准数据集用于建立索引，810的训练集和410的查询集. 实验数据集的具体描述如表1所述.表1 实验数据集描述数据集大小基准数据集910 训练集810 查询集 410由于SIFT 描述子是浮点型的向量，作者采用文献[7]提供的开源代码得到原始数据集对应的二进制码数据集，每个二进制码为128维. 在实验中，首先由训练集计算二进制码各位的相关性并学习投影向量. 在性能对比时，训练集和基准数据集没有重合，以保证算法的普适性.为了验证本文提出的数据依赖的多索引哈希算法（Data-Oriented Multi-Index Hashing ，DOMIH ）的性能，本文与多索引哈希算法（Multi-Index Hashing ，MIH ）[7]和数据驱动的多索引哈希算法(Data Driven Multi-Index Hashing ，DDMIH) [11]进行实验对比. 数据驱动的多索引哈希算法把二进制码划分为多个不连续且不重合的子串，以去除数据的相关性.实验的硬件环境如下：Intel Xeon E5-2620*2(2.00 GHz, 7.2GT/s, 15M cache, 6cores)，64G 内存，上述三个算法都在相同的软硬件环境下运行. 由于这三个算法都返回查询的精确最近邻，因此它们具有相同的精度[11]. 所以在性能对比中，本文主要比较它们的平均查询时间和扩展性.第4期马艳萍等：数据依赖的多索引哈希算法 1812.2 训练集大小对算法的影响由于本文构建训练集计算二进制码各位的相关性并学习自适应投影向量，那么训练集的大小对算法的性能有一定的影响. 直观上地，训练集越大得到的投影向量越能反应二进制码各位的相关性，算法的性能越好；训练集越小则算法的性能较差. 但是训练集越大计算协方差矩阵的时间就越长，即使这些操作是离线完成不影响在线查询时间. 表2 展示了随着训练集大小的变化本文算法的@1000recall NN 值.@1000recall NN 值度量索引算法返回的前1000个候选结果中正确结果的个数，即召回率. @1000recall NN定义如下：_1000_1000@1000_1000DOMIH NN Linear NN recall NN Linear NN∩= , (7) 其中_1000DOMIH NN 是本文算法返回的前1000个候选结果，即没有根据与查询之间的海明距离对候选结果排序；_1000Linear NN 是线性查找算法返回的前1000个结果，即精确的1000近邻. 对于每个查询，本文计算它的@1000recall NN 值，然后对所有查询求均值.表2 训练集大小对算法性能的影响，基准数据集为910.训练集大小310410510610 710810@1000recall NN 0.4470.5240.5720.623 0.6260.627通过表2 可以看出当训练集中元素个数从310增加到810时，本文算法的@1000recall NN 值不断提升. 当训练集从310增加到610时，@1000recall NN 值的增加幅度很大；当训练集从610增加到810时，@1000recall NN 值的增加幅度很小；即当训练集的大小为610时，@1000recall NN 值趋于稳定. 综合考虑算法精度和时间性能，本文把训练集的大小设置为610.2.3 算法有效性和扩展性验证为了验证本文算法的有效性，本文首先根据公式(6)对比DOMIH 、MIH 和DDMIH 中各个哈希表的数据分布情况；然后对比随着基准数据集和返回结果数量的增加，这三个算法对单查询的平均响应时间. 由于基准数据集的大小为910，那么每个二进制串的长度为9102log 32≈错误！未找到引用源。

二进制乘法问题分治法伪代码

二进制乘法问题分治法伪代码以下是一个使用分治法解决二进制乘法问题的伪代码示例：```Function binaryMultiplication(a, b):// 转换为二进制字符串binaryA = decToBinary(a)binaryB = decToBinary(b)// 补零maxLen = max(length(binaryA), length(binaryB))binaryA = zeroPad(binaryA, maxLen)binaryB = zeroPad(binaryB, maxLen)// 递归基if length(binaryA) = 1 or length(binaryB) = 1:return binaryA * binaryB// 将二进制数分成两半mid = length(binaryA) / 2// 分别取出左右两部分leftA, rightA = split(binaryA, mid)leftB, rightB = split(binaryB, mid)// 递归计算子问题p1 = binaryMultiplication(leftA, leftB)p2 = binaryMultiplication(rightA, rightB)p3 = binaryMultiplication(leftA + rightA, leftB + rightB) - p1 - p2// 计算最终结果result = (p1 << (2 * mid)) + (p3 << mid) + p2return result```在这个伪代码中，使用分治法将二进制乘法问题转化为更小规模的子问题。

首先，将输入的十进制数字转换为二进制字符串，并进行补零，使得两个二进制数的位数相等。

然后，递归地将二进制数分成两半，分别计算左半部分与右半部分的乘积以及左半部分与右半部分相加的乘积。

计算机专业英语第二章

标点符号
Seven-and Eight-Bit Codes
排列
With 7 bits , it’s possible to provide 128 变化， different arrangements; With 8 bits , 256 变种 variations are possible. They are sufficient number to code 小写字母 lower-case-letters (26) , and a large number of other characters (28) .
Registers
跟踪

全部的，全面的
A register is a storage location inside the processor . Register in the control unit are used to keep track of the overall status of the program that is running . Control unit registers store information such as the current instruction .
2-2 WHAT IS A PROCESSOR

2-2
什么是处理器
Notes:

Instruction set 指令系统 Processor 处理器 Operation 操作 Operand 操作码 Clock 时钟 Megahertz(MHz) 兆赫 Word size 字长

Seven-and Eight-Bit Codes

The 7-bit American Standard Code for Information Interchange (ASCII) is widely used in data communications work and is by far the most popular code used to represent data internally in personal computers . by far 修饰比较级、最高级，强调数量、程度等，意为“……得多，最……”。

Secure method of processing data

专利名称：Secure method of processing data发明人：Alain Patey,Herve Chabanne,Julien Bringer申请号：US14409027申请日：20130617公开号：US09350731B2公开日：20160524专利内容由知识产权出版社提供专利附图：摘要：The invention relates to a secure method of processing data in which method is implemented the evaluation of a function that may be written as a linear combination of sub-functions with two binary inputs, in which a client and a server each possess a binary code, comprising n indexed bits, the method comprising the evaluation of the functionwith the binary codes of the client and of the server as inputs, without one of the client or the server obtaining information about the code of the other, the method being characterized in that it comprises the following steps: —the server randomly generates n indexed values and calculates the linear combination of these values with the same linear combination as that applied to the sub-functions to obtain the function, —the client implements, for each bit of his binary code, a technique of unconscious transfer to obtain from the server an intermediate data item comprising the randomly generated value of same index as the bit of the code of the client, increased by the value of the corresponding sub-function evaluated at the bit of same index of the code of the server and at said bit of his binary code, and —the client performs a linear combination of the intermediate data for all the bits of his binary code, with the same linear combination as that applied to the sub-functions to obtain the function, in such a way as to obtain a final result comprising the linear combination of the randomly generated values, increased by the evaluation of the function at the two binary codes.申请人：MORPHO地址：Issy-les-Moulineaux FR国籍：FR代理机构：Oblon, McClelland, Maier & Neustadt, L.L.P.更多信息请下载全文后查看。

2.5 信息的二进制编码

BCD数的加法(Addition of BCD Digits)
4
数字逻辑设计及应用 ( Digital Logic Design and Applications )
5
数字逻辑设计及应用 ( Digital Logic Design and Applications )
2.5.3 十进制数的二进制编码
2.5 .3 十进制数的二进制编码
(Binary Codes for Decimal Numbers) 如何用 4位二进制码（4-bit Binary code）表示 1位
十进制码（1-bit Decimal number )？ —— BCD码(Binary Coded Decimal ）
用了7位，码字的前2位表示十进制数是0-4还是5-9 ，后5位表示指定范围内的哪个数
11
One Hot Code（独热码）
1-out-of-10 code 又称10中取1码，每个编码字均为10位在这10位中只有1位为1 其他9位均为0，用于控制系统中
12
BCD codes
Examples: use BCD code for decimal numbers A = 1946 8421 code : A = 0001 1001 0100 0110 2421 code : A = 0001 1111 0100 1100 Excess-3 code: A = 0100 1100 0111 1001
6
数字逻辑设计及应用 ( Digital Logic Design and Applications )
7
BCD Codes
8421 Code 自然二进制编码是一种加权码因为每个十进制数码都可以由其码字求得，码字的每一位有固定的权从左到右各位的权分别为8、4、2、1

Binarized Statistical Image Features

BSIF:Binarized Statistical Image Features Juho Kannala and Esa RahtuUniversity of Oulu,FinlandAbstractThis paper proposes a method for constructing lo-cal image descriptors which efﬁciently encode texture information and are suitable for histogram based rep-resentation of image regions.The method computes a binary code for each pixel by linearly projecting local image patches onto a subspace,whose basis vectors are learnt from natural images via independent component analysis,and by binarizing the coordinates in this basis via thresholding.The length of the binary code string is determined by the number of basis vectors.Image re-gions can be conveniently represented by histograms of pixels’binary codes.Our method is inspired by other descriptors which produce binary codes,such as local binary pattern and local phase quantization.However, instead of heuristic code constructions,the proposed approach is based on statistics of natural images and this improves its modeling capacity.The experimental results show that our method improves accuracy in tex-ture recognition tasks compared to the state-of-the-art. 1IntroductionLocal image descriptors have been under extensive investigation during the recent years and many impor-tant developments have been acquired.Nowadays local image descriptors are standard tools which provide im-age features for many computer vision applications.For example,local descriptors together with interest region detectors allow extraction and description of image re-gions which are used for wide baseline image matching, in e.g.multi-view reconstruction.Also,visual vocabu-laries,based on descriptors,are predominantly used in image retrieval and recognition tasks,like particular ob-ject retrieval and object class recognition.Further,local image descriptors are widely used in texture recognition and its applications.There are various local image descriptors proposed in literature.For example,interest regions are typically represented using descriptors like SIFT[8],SURF[3], or BRIEF[4],and their variants.Further,there are sev-eral image descriptors originally designed for texture description and classiﬁcation,such as local binary pat-tern(LBP)[9],local phase quantization(LPQ)[10,2] and basic image features(BIF)[5].Some of them,or their variants,have become increasingly popular also in other applications,like face identiﬁcation[1,2]and ac-tion recognition from videos[12].In this paper,we propose an approach which is in-spired by LBP and LPQ methodologies.These methods describe each pixel’s neighborhood by a binary code which is obtained byﬁrst convolving the image with a set of linearﬁlters and then binarizing theﬁlter re-sponses.The bits in the code string correspond to bina-rized responses of differentﬁlters.However,in contrast to earlier approaches,such as LBP and LPQ,we do not use a manually predeﬁned set ofﬁlters but learn theﬁl-ters by utilizing statistics of natural images.Our texture and face recognition experiments show that the proposed approach gives a better overall per-formance than the popular and widely used comparison methods LBP and LPQ.Further,our results are obtained by using aﬁxed set ofﬁlters learnt from a small set of natural images,which shows that pre-learntﬁlters can be used for different applications.Nevertheless,unlike comparison methods,our approach provides an option of application-speciﬁc learning,which might be poten-tially useful for describing images that have unusual characteristics,such as certain medical images.2MethodOverview.Our method computes a binary code string for the pixels of a given image.The code value of a pixel is considered as a local descriptor of the image intensity pattern in the pixel’s surroundings.Further, histograms of pixels’code values allow to characterize texture properties within image subregions.Thus,our descriptor can be used in texture recognition tasks in a similar manner as local binary patterns[9]or quantized local phase values[10].The value of each element(i.e.bit)in our binary code string is computed by binarizing the response of a lin-earﬁlter with a threshold at zero.Each bit is associ-ated with a differentﬁlter and the desired length of the bit string determines the number ofﬁlters used.The set ofﬁlters is learnt from a training set of natural im-age patches by maximizing the statistical independence of theﬁlter responses[6].Hence,statistical properties of natural image patches determine the descriptors and therefore we call them binarized statistical image fea-tures(BSIF).The details of learning the linearﬁlters follow[6]and they are brieﬂy described below. Details.Given an image patch X of size l×l pixels and a linearﬁlter W i of the same size,theﬁlter response s i is obtained bys i= u,v W i(u,v)X(u,v)=w⊤i x,(1) where vector notation is introduced in the latter stage, i.e.,vectors w and x contain the pixels of W i and X. The binarized feature b i is obtained by setting b i=1 if s i>0and b i=0otherwise.Given n linearﬁlters W i,we may stack them to a matrix W of size n×l2 and compute all responses at once,i.e.,s=Wx and we obtain the bit string b by binarizing each element s i of s as above.Thus,given the linear feature detectors W i,computation of the bit string b is straightforward. Also,it is clear that the bit strings for all image patches of size l×l,surrounding each pixel of an image,can be computed conveniently by n convolutions.In order to obtain a useful set ofﬁlters W i we apply the ideas of[6]and estimate theﬁlters by maximizing the statistical independence of s i.In general,this ap-proach provides good features for image processing[6]. Furthermore,in our case,the independence of s i pro-vides justiﬁcation for the proposed independent quanti-zation of the elements of the response vector s.Thus, costly vector quantization,used e.g.in[14],is not nec-essary here for obtaining a discrete texton vocabulary.However,in order to use standard independent com-ponent analysis(ICA)algorithms for estimating the in-dependent components,one has to decompose theﬁlter matrix W into two parts bys=Wx=UVx=Uz,(2) where z=Vx,and U is a n×n square matrix which will be estimated via ICA,and matrix V performs the canonical preprocessing,i.e.simultaneous whitening and dimension reduction of training samples x[6].In short,the canonical preprocessing uses principal component analysis as follows.Given a training set of image patches randomly sampled from natural images, the patches areﬁrst made zero-mean(i.e.the mean in-tensity of each patch is subtracted)and then theirdi-Figure1.Learntﬁlters of size9×9. mension is reduced by keeping only the nﬁrst princi-pal components which are further divided by their stan-dard deviation to get whitened data samples z.In de-tail,given the eigendecomposition C=EDE⊤of the covariance matrix C of samples x,the matrix V is de-ﬁned byV= D−1/2E⊤ 1:n,(3) where the main diagonal of D contains the eigenvalues of C in descending order,and(·)1:n denotes theﬁrst n rows of the matrix in parenthesis.Then,given the zero-mean whitened data samples z,one may use standard independent component analy-sis algorithms to estimate an orthogonal matrix U with which one yields the independent components s of the training data[7].In other words,since z=U−1s, the independent components allow to represent the data samples z as a linear superposition of the basis vectors deﬁned by the columns of U−1.Finally,given U and V,one obtains theﬁlter matrix W=UV,which can be directly used for computing BSIF features.Implementation.In all the experiments of this paper, we used the sameﬁlters learnt from a set of13natural images provided by the authors of[6].Before random sampling of image patches for learning,the image in-tensities were normalized to have a zero mean and unit variance.As described above,there are two parameters in our BSIF descriptor:theﬁlter size l and the length n of the bit string.We learnt theﬁlters W using sev-eral different choices of parameter values,each set of ﬁlters was learnt using50000image patches.Learning was conducted by the three-stage process detailed in the previous subsection:(a)subtraction of the mean inten-sity of each patch,(b)dimension reduction and whiten-ing via principal component analysis,and(c)estimation of independent components.Theﬁlters obtained with l=9,n=8are illustrated in Figure1.In addition,our implementation of BSIF features is available online.1 1http://www.cse.oulu.fi/Downloads/BSIFFigure2.Samples from Outex database(top)and corresponding BSIF codes.3ExperimentsIn this section we will asses the proposed method in two canonical texture recognition applications:texture classiﬁcation and face recognition.For texture classiﬁ-cation,we use Outex and CUReT benchmark datasets, for which we adopt the train-test splits deﬁned in Ou-tex test suite00002and in[14],respectively.Outex dataset contains24texture types and368images per class,while the CUReT database consists of61textures and205images per class.Some examples and corre-sponding BSIF code images are shown in Figures2and 3.The classiﬁcation is performed using nearest neigh-bor classiﬁer withχ2distance metric.The baseline for the experiments is formed by Local Binary Patterns(LBP)[9],BIF-column(BIFc)[5],and Local Phase Quantization(LPQ)[10]methods.We use standard8bit coding for LBP and LPQ,which results in a feature vector with256elements.For BIFc we apply the parameters described in the original paper.Hence, BIFc applies4different scales with6codewords per scale,resulting in descriptor with1296elements.The classiﬁcation accuracies with differentﬁlter sizes are reported in Figures5(a)and5(b).The re-sults indicate that the proposed descriptor is consis-tently better than LBP or LPQ over a range of differ-entﬁlter sizes.Interestingly,already7bit version of BSIF outperforms all baselines in Outex and LPQ in pared to BIFc descriptor,the new method performs clearly better in Outex.In the case of CUReT datababase,BIFc gives1.5percent better accuracy than 8bit BSIF,but the difference vanishes when the descrip-tor length is increased to be equivalent to BIFc.The im-ages in CUReT are taken from several viewing angles and hence they contain some rotations.Since BIFc is rotation invariant,it is understandable that it performs well in this experiment.However,BSIF reaches the same performance,even if it was not particularly de-signed to be rotation invariant.In the face recognition experiment we apply the Face Recognition Grand Challenge(FRGC)test1.0.4[11]. The FRGC database is divided into probe andgalleryFigure3.Samples from CUReT database(top)and corresponding BSIFcodes.Figure4.A sample gallery image and twoprobe images images from FRGC(top),and corresponding BSIF codes.The blurin the probe images is clearly observable. sets,which represent152subjects.There are exactly 1gallery image and2-7probe images per subject,to-taling152images in the gallery and608images in the probe set.The images in the gallery are acquired with good quality camera under controlled conditions,while probe images are taken with pocket digital camera in uncontrolled conditions.Therefore,probe images con-tain considerable variations in lightning,facial expres-sion,and blur.Some examples and the corresponding BSIF code images are shown in Figure4.For the recognition we apply the procedure described in[1]:the face image isﬁrst divided into8×8non-overlapping rectangular regions and a given descriptor is computed independently within each of these regions. Finally,the descriptors from different regions are con-catenated to a global description of the face.The clas-siﬁcation is performed using nearest neighbor classiﬁer withχ2distance metric.Also,as in[2],we apply the illumination normalization proposed in[13].The average face recognition accuracies are shown in Figure5(c).The effect of blurring is clearly ob-servable in the BSIF results.If the number ofﬁlters is increased while keeping the sizeﬁxed,more high fre-quency information will be included into the descrip-(a)Outex(b)CUReT(c)FRGCFigure5.The average classiﬁcation accuracies for different benchmark databases.Note:Since BIFc is a multiresolution method,the corresponding results are indicated by horizontal lines.tor.Since high frequencies are particularly disturbed by blurring,it will affect the performance of such combi-nations.Hence,we need to enlarge theﬁlter size with respect to the code length in order to cope with blur-ring.The6and7bit version of BSIF give good re-sults already with7×7ﬁlter,losing only3percents to the blur invariant LPQ.When increasing the descriptor length to8bit and above,we reach approximately the same performance as LPQ with13×13ﬁlters.Fur-thermore,already6bit BSIF outperforms LBP over the wide range ofﬁlter sizes.4ConclusionIn this paper we presented a method for constructing local texture descriptors,based on independent compo-nent analysis and efﬁcient scalar quantization scheme. The proposed algorithm results in a binary code for each pixel,which can be subsequently used to construct a convenient histogram representation for image areas. The key idea in the approach is to apply learning,in-stead of manual tuning,to obtain statistically meaning-ful representation of the data,which enables efﬁcient information encoding using simple element-wise quan-tization.Learning provides also an easy andﬂexible way to adjust the descriptor length and to adapt to ap-plications with unusual image characteristics.In texture classiﬁcation experiments,the new BSIF descriptor clearly outperformed the state-of-the-art baseline methods with equivalent descriptor length.In-terestingly,also more compact versions of BSIF re-sulted in better accuracy than some of the baselines. Moreover,the proposed method was tested in a face recognition application,where it resulted in equal per-formance to the state-of-the-art descriptors.Although some of the test images were blurred and imperfectly aligned,BSIF resulted in similar performance as specif-ically designed rotation and blur invariant methods.This indicates the tolerance of BSIF descriptor to im-age degradations appearing in practice. References[1]T.Ahonen et al.Face description with local binary pat-terns:Application to face recognition.TPAMI,2006.[2]T.Ahonen et al.Recognition of blurred faces using localphase quantization.In ICPR,2008.[3]H.Bay et al.Speeded-up robust features(SURF).CVIU,2008.[4]M.Calonder et al.BRIEF:Binary robust independentelementary features.In ECCV,2010.[5]M.Crosier and L.Grifﬁing basic image featuresfor texture classiﬁcation.IJCV,3(88):447–460,2010.[6] A.Hyv¨a rinen et al.Natural Image Statistics.Springer,2009.[7] A.Hyv¨a rinen and E.Oja.Independent component anal-ysis:algorithms and applications.Neural Networks, 2000.[8] D.G.Lowe.Distinctive image features from scale-invariant keypoints.IJCV,2004.[9]T.Ojala et al.Multiresolution gray-scale and rotationinvariant texture classiﬁcation with local binary pat-terns.TPAMI,7(24):971–987,2002.[10]V.Ojansivu and J.Heikkil¨a.Blur insensitive textureclassiﬁcation using local phase quantization.In ISP, 2008.[11]P.Phillips et al.Overview of the face recognition grandchallenge.2005.[12]M.Pietik¨a inen et puter Vision Using Local Bi-nary Patterns.Springer,2011.[13]X.Tan and B.Triggs.Enhanced local texture featuresets for face recognition under difﬁcult lighting condi-tions.In AMFG,2007.[14]M.Varma and A.Zisserman.A statistical approachto texture classiﬁcation from single images.IJCV, 62(1):61–81,2005.。

ctft题目二进制数据解密

ctft题目二进制数据解密关于二进制数据的解密，需要根据具体的情况来分析，如何理解数据、如何处理数据等等。

这里提供一个基本的思路：1. 首先需要理解二进制数据的结构和含义，因为每个位都代表了不同的权值，所以需要清楚二进制数据的每一位代表的意义和含义。

2. 其次需要根据题目的提示或者其他线索，判断题目中使用的加密算法或者编码方式，例如常见的base64、hex、rot13等等。

3. 根据上面的分析，写出解密代码并验证是否能够得到正确的结果。

举个例子，假设题目给出的是一段被base64编码的二进制数据，那么可以使用Python的base64库进行解码，代码如下：```pythonimport base64binary_data = "010101011001100101011101011011010000110100101110011011000 11011010000110000101110011001100010110010001110011011011110110111000100000011101000110010101110010011100110110010101 1011100110011001011010011010010110111001101100011011000110 1111011101000010000001011100011010000110010101101110011010 0101101110011101110110111101110100"# 将二进制数据转换为bytes类型bytes_data = bytes(int(binary_data[i:i+8], 2) for i in range(0, len(binary_data), 8))# base64解码decoded_data = base64.b64decode(bytes_data)# 将解码结果转换为字符串result = decoded_data.decode('utf-8')print(result)```上述代码将原始的二进制数据转换为bytes类型，然后使用base64库进行解码，最后将解码结果转换为字符串输出。

专业外语-通信编码第13课

on the bandwidth of the path，so bandwidth is a very important ingredient in data communications．带宽是数据通信中很重要的部分，因为信道容量取决于信道带宽。
注：去掉Because或so。
科技英语常见语法错误
Text Tour
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In the data communications world, data generally are defined as information that is stored in digital form. The word data is plural; a signal unit of data is called a datum. Data communications is the process of transferring digital information (usually in binary form) between two or more points. Information is defined as knowledge or intelligence. Information that has been processed, organized, and stored is called data. Data can be alphabetic, numeric, or symbolic in nature and consist of any one or a combination of the following: binary-coded alpha/numeric symbols, microprocessor op-codes, control codes, user addresses, program data, or database information.

Nonbinary quantum codes

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ERIC M. RAINS
self-orthogonality; this means, in particular, that the existence of an MDS code of length n and minimum distance d need not imply the existence of MDS codes of any smaller length with that minimum distance. Thus it no longer suces to consider the largest possible length. Sometimes, however, one can safely shorten a quantum MDS code; indeed, associated to any such (symplectic) code, we construct a classical code, the codewords of which correspond to di erent valid shortenings. This construction applies to other codes as well, even those that are not self-orthogonal.
Introduction
Most of the work to date on quantum error correcting codes has concentrated on binary codes, both because this is the simplest case, and because such codes are likely to be the most useful. However, there are some applications for which nonbinary QECCs would be more useful (e.g., for proof-of-concept implementation in certain ion trap models (R. La amme, personal communication)). Also, codes over alphabets of size 2l could be useful for constructing easily decodable binary codes, via concatenation. Finally, regardless of any practical interest, nonbinary codes are likely to be of considerable theoretical interest, just as in classical coding theory. Thus the present work, which admittedly is more a collection of looselyrelated results than any sort of attempt at a complete theory of nonbinary quantum codes.

袁学东-四川大学数字逻辑第2章Number Systems Operations

Practice problem: convert 367.2368to binary then hexadecimal Solution 367.2368=011,110,111.010,011,1102 011,110,111.010,011,1102=0,1111,0111.0100,1111,02=F7.4F16
（LSB）
（MSB）
2 Number System Conversion
Decimal to Binary Conversion
•Fractional Radix Conversion, Successive Multiplication
•(小数基转换，逐次乘法) [乘积中的整数部分成为新基下的数，
Convert the integer portion by successive division
1.Divide 23 by 8 (LSB) 2.Divide 2 by 8 (MSB)
Convert te fraction portion by successive multiplication
(数字系统以离散方式表示信息，数制系统提供了由数字系统处理量化信息的一种方法)
– Positional Number Systems – Number system conversion – Binary Codes – Arithmetic
Number Systems - Decimal
“base” 10 (radix is 10) 10 digits: 0...9
Let r=radix or base of a number system; 数制的基或基数 Let c=character from the character set of the radix; 该基的字符集合中的字符 Let N=number to be represented in radix;

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读书破万卷下笔如有神信息论与编码理论bits (binary digits)比natural digits自然entropy function熵函数Theories ofInformationprobability vector可能向conditional entropy条件熵and Codingdiscrete memory channel离散记忆信transition probability过渡可能性output产marginal distritution边际分布介绍第一章mutual information互信heuristic启发joint entropy联合熵Introduction Chapter 1 Venn diagram维恩Markov chain马尔可夫链information theory信息definite function限定函coding theory编码理tandem串emit发data-processing configuration数据过程配bit字convex combination凸组binary二进manipulation操binary symmetric source二进制对称shorthand速记binary symmetric channel二进制对称信communication system通信系统raw bit error probability 原始字节错误率continuous source outputs 连续信息输出encode编码coder 编码员bit error probability 字节错误率map 映射noise 噪音destination目标redundant 冗余data-processing theorem 数据过程定理cross check 相互校验discrete quantization 离散量化codding algorithm 编码算法refinement /精炼改进error pattern 错误模式density密度synthesis 综合mean value theorem 中值定理Hamming code汉明码superficial resemblance 表面相似single-error-correcting code 单独错误校正码mesh网格rate速率differential entropy 微分熵binary entropy function 二进制熵函数Jensen inequality 琴生不等式capacity能量determinate channel确定信道channel coding theory信道编码理论第二章信息理论Information TheoryChapter 2读书破万卷下笔如有神第三章离散无记忆信第四章离散无记忆信源和扭曲道和容量成本率方程方程Chapter 4 Discrete DiscreteMemoryless Sources and Memory less Channels Chapter 3their Rate-Distortion Equations and their Capacity-Cost Equationssource alphabetinput sign system源字母输入符号系discrete memoryless sourcesoutput sign system输出符号系离散无记忆信source statisticsimagine想统计object signmemoryless assumption目标符无记忆假distortionaverage cost平均成扭distortion measurecapacity-cost equation扭曲容量成本方average distortiontest-source平均扭验证源test channeln-dimensional admissible test sources维容许验证测试通distortion rate扭曲admissible cost容许成source coding theorem源编码定r-symmetry对backwards test channel向后测试通道rate of system系统比率Hamming distortion measure 哈莫名扭曲度rates above channel capacity 超过信道容量率error probability distortion rate 错误扭曲率length 长data-compression theorem 数据压缩定理bits per symbol 每个符号的比特destination symbols 目的符号decoding rule 编码规则data compression scheme 数据压缩系统distinct code 区别代码penalty function 罚函数indicator function 指示函数unrestricted sum 无限制和random coding 随机编码inner sum内部和expected value期望值weak law of large numbers 弱大数定律decoding sphere 编码范围第五章高斯信道和信源Chapter 5 Gaussian Channel and Sourcevoltage 伏特transmit 传送signal信号．读书破万卷下笔如有神source statisticswatts信源统rate of transmissiondissipate传送耗conflictjoule焦冲source-channel coding theoremwhite Gaussian noise process白高斯噪声过理noise spectral density噪声错误密data-processing theorem数据传输定bandwidth带intermediate vector中间向band-limited波段限worst-case distortion最坏扭power-limited功率限per-symbol basis每个符号基n-th capacity-cost function项容量成decomposition分函transmitted codingsquared-error传送编平方错affordoinkoverallcapacity-costfunction总的容量成本负density数噪声密tradeoff交arithmetic-geometric average value几何均算realizable region可实现区Gaussiandiscrete-timememoryless离散时间无记standpoint观点source高斯信源mean-squared error criterion第一部分访问gaussion distribution 高斯分布per-symbol均值平方错误标准第七章Gaussiansource高斯信源每个符先进标题per-symbol mean-squared distortion号均值平方扭曲Chapter 7 Survey of Advanced Topics for 信道编码第六章信源-Part One理论twin pearls孪生珍珠finite Abelian commutative group有限阿贝尔交换群Source-Channel Coding Theory Chapter 6 ergodic random process各态经历随机过程information source 信息源entropy熵noisy source 噪声源additive ergodic noise channel添加各态噪音信data processing 道数据处理asymptotic average property quantization 量子化渐进线均分性质Gaussian process modulation 高斯过程调节multiterminal channel successive block多终端信道连续块feedback emit channel output symbols反馈发出信道输出符号seeder 发送人one-to-one correspondence 一对一通信receiver接受人test source 实验来源multi-access channel 多通道信道source sequence 信源序列erasure symbol 擦掉符号destination sequence 目的序列contradiction矛盾读书破万卷下笔如有神rate比率practical standpoint实际观broadcast channel广播信generator matrix生成矩capacity region容量区row space行空high degree of symmetry 高对称parity-check matrix奇偶校验矩test sources测试信canonical form规范形input signal channel输入符号信error pattern错误模global maximum全局最coset傍additive ergodic noise添加各态噪symmetric channel对称信reliability exponent of channel信道的可靠性Hamming wight汉明table lookupcritical rate关键表格查standard arraylinear code线性标准排italicizedtime-varying convolutional强时间改变卷积metric spaceencoder-channel-decoder度量空编信译Hamming distanceouter channel汉明距外部信interectinner code内部编穿minimum weightouter code最小权外部编single-error-correctingweak converse弱颠单错误校perfect codesstrong converse强颠完全repetition codesterm术重复binary Hamming codesrate of transmission二进制汉明传输detecterror exponent错误指检e-correctingstrong similarity电子校强近H-detectingrather duality选择两重检Fparity-check matrixdistortion rate theory扭曲率理类似校验矩double-error-detectingsource coding method源编码双错误检weight enumeratorsingle-letter distortion measure单字母扭曲度权重计数homomorphismimplication含同multiplicative groupconfiguration轮趋于增加组indeterminate error probability 错误可能性不确定half-plane bound 半平面界reception接待discrete-time stable离散时间稳定高第九章循环码斯信源stable Gaussian sequence 稳定高斯序列spectral density 谱密度Chapter 9 Cyclic Codes tree codes树码burst errors突发性错误definition of innocuous-appearing 表面无害定理cyclic shift 循环位移第八章线性码trivial cyclic 一般循环no-information code无信息码Linear codesChapter 8读书破万卷下笔如有神depth-3 interleavingsingle-parity-check code单等价校验度交interleaving operationno-equivalent code无等价交错操elaborate algorithmright cyclic shift右循环位复杂算Fire codegenerating function法尔母函Fire constructiongenerator polynomial法尔结生成多项burst-trapping algorithmreciprocal爆发阻塞算互惠burst-error-correcting codecyclic property爆发错误校正循环性decomposition分left-justified左对transmitted codeword传送编trap陷阱，阻shift-register encoder转换登记编burst-error pattern爆发错误模flip-flops adders突变加法Meggitt lemma米戈蒂引constant multipliers常数乘法shift-register切换显delay延circuit环impulse response脉冲响leftmost flip-flop y香最左面的突state vector状态向量state polynomial 状态多项式input stream 输入流reverse order 反顺序第十章农码和相关linear recursion 线性递归rightmost flip-flop 最右面的突变的码mod-2 adder 模2加法器cyclic 循环two-field二域Chapter 10 Shannon Codes and Related primitive polynomial 原始多项式Codes decoding cycle 译码循环circular journey 循环旅程Shannon code香农码lower shift register 低位移寄存器Vandermonde determinant theory范德蒙德行列式burst-error-correcting 突发错误校正理论pattern 模式original parity-check matrix 初始相同检验矩burst description 突发描述阵location 位置minimal polynomial 最小多项式ambiguity 含糊不清key equation关键方程zero run零操作discrete Fourier transform 离散傅里叶变换burst-error correcting code 突发错误校正码time-domain 时间领域Abramson bounds 阿布拉门逊界frequency-domain 频数领域strict Abramson bound严格阿布拉门逊subtlety 细致界time shift 时间转换weak Abramson bound 弱阿布拉门逊界phase shift 相位转换Reiger bound Reiger界support set 支撑集合loose松散evaluator polynomial 评估多项式Abramson code 阿布拉门逊码formal derivative规范派生interleaving 交错frequency-domain recursion 频数主导递归De-interleaving交错De读书破万卷下笔如有神frequency-domainsubscript下频数Golay codelocator polynomial戈莱定位多项extended Golay codeerror pattern扩展戈莱错误模byte implementationtwisted error pattern字节工扭曲错误模table loopreduced mode表复原模error location错误定位error-evaluator polynomial 错误评估多项式Euclid algorithm 欧几里得算法第十一章卷积码quotient 份额facilitate促进time-domain approach 时间主导方法Chapter 11 Convolution Codes error-locator 错误定位器trial and error 试错法matrix polynomial矩阵多项pseudocode fragment伪码片shift-register approach转移登记方recursion递scalar matrix纯量矩abnormal反state-diagram approach状态图方elaborate theory复杂理memory记忆，内multiple-error-correcting linear code多倍错误校正constraint length约束长性k-tudecode character代码字L-th section截平maximum-distance separable codes最大距离可分state-diagram状态interpolation property插值法性track轨道，足information set信息集trellis diagram格子interpolation algorithm插值算survivors幸存recursive completion递归结Viterbi decoding algorithm维特比译码算pseudocode伪path weight enumerator路权重concatenated coding 连锁elaborate labels复杂burst-error-correction爆发错误校complete path enumerator完全路径depict描error events错误时间unfactor 非因子first error probability 最早错误可能性flaw缺陷bit error probability 比特错误可能性erasure symbol 擦掉符号free distance自由距离transmitted symbol 传递符号sequential decoding algorithm 连续译码算法enlarge扩大tree diagram 树形图minimum-distance decoding 最小距离译码binary tree 二进制树erasure set擦除集合bifurcation 分枝erasure-location polynomial擦除位置多项式abandoned 抛弃errors and erasures-locator-polynomial错误擦除位置多stack algorithm 栈算法项式Fano algorithm 法诺算法errors-and-erasures-evaluator 错误擦除评估多different lengths 差异长度polynomial项式flowchart流程图modified syndrome polynomial 修正综合多项式polynomial multiplication多项式乘法．读书破万卷下笔如有神第十二章变量长度源编码Chapter 12 Variable-length Source Codingmethod of variable-length source 变量长度源编码coding法string of length k 长度串kempty string 空字符串substring子串。

Abend Codes

Abend CodesThe information below was extracted verbatim from File #134 of the CBTtape. All that has been done was the removal of the TSO HELP control information.The first column contains the System or User Abend Code (Snnn orUnnn). The second column contains a reason code. The third columncontains the text explaining why the Abend may have occurred.If you would prefer to download this information as an Adobe® PortableDocument File, use this link: sabends.tar.gz [MD5:7B11271AA7F409853341D548E75222A7].S001 - AN INPUT/OUTPUT ERROR CONDITION WAS ENCOUNTERED DURINGEXECUTION OF A CHECK/GET/PUT MACRO INSTRUCTION. EITHER NOSYNADROUTINE WAS PROVIDED TO HANDLE THE ERROR, OR DCB=EROPT=ABEWASSPECIFIED OR DEFAULTED. ***IF THE REGISTER 15 RETURN CODE IS AVAILABLE, SUPPLY IT INTHE******S001 OPERAND FOR MORE SPECIFIC INFORMATION: H ABENDO(S001-RC)**--POSSIBLE CAUSE-- INPUT RECORD DESCRIBED INCORRECTLY, LENGTH ERROR TRIED TO READ AFTER ENCOUNTERING END OF FILE RECFM V IS INCOMPATIBLE WITH TRTCH ET TRIED TO WRITE ON AN INPUT FILE READ INTO A TABLE WHOSE SUBSCRIPT WAS ZERO INCORRECT LABEL PARAMETER TRTCH PARM WAS WRONG TAPE BEING READ IN WRONG DENSITY DIRECTORY OF PDS WAS OVERWRITTEN NSL LABEL HAD INCORRECT DSNAME, OPERATOR CANCELLED TRUE I/O FAILURE, UCB SHOW REDUNDANCY HARDWARE ERROR - BAD TAPE OR TAPE DRIVE SECONDARY SPACE ALLOCATION FOR DASD OUTPUT FILE TOO SMALL (SEE SB37)COBOL - INCORRECT USE OF BLOCK CONTAINS CLAUSE - HAD RECORDING MODE F WHEN GENERATED, BUT NOT WHEN READS001 - 01 - AN I/O ERROR OCCURRED DURING BDAM CREATE, BSAM, BISAM,QSAM, OR BDAM AND NO SYNAD EXIT WAS SPECIFIED BY THE USER.S001 - 02 - AN ERROR WAS ENCOUNTERED WHILE ATTEMPTING TO CLOSETHE DATASET. S001 - 03 - FOR QSAM, AN ERROR WAS ENCOUNTERED THAT COULD NOT BEACCEPTED. S001 - 04 - FOR QSAM, ABE OR AN INVALID VALUE FOR EROPT PARAMETER INTHE DCB AND/OR NO ERROR HANDLING (SYNAD) EXIT WAS SPECIFIED.S001 - 05 - FOR QSAM, A GET WAS ISSUED AFTER END-OF-FILE.S002 - RECORD IS GREATER THAN 32,768 BYTES, EXCEEDS MAXIMUM TRACKLENGTH OR STATED BLOCKSIZE, COULD NOT BE CONTAINED IN ONEEXTENT, OR TOO MANY TRACKS SPECIFIED FOR CYLINDER OVERFLOW.***IF THE REGISTER 15 RETURN CODE IS AVAILABLE, SUPPLY IT INTHE******S002 OPERAND FOR MORE SPECIFIC INFORMATION: H ABENDO(S002-RC)**--POSSIBLE CAUSE-- DCB HAD THE WRONG BLOCK SIZE IEHMOVE - ATTEMPT TO RENAME DATA SET WHEN NEW NAME ALREADYEXISTSWRONG RECORD FORMAT SPECIFIED IN JCL S002 - 04 - AN INVALID RECORD WAS ENCOUNTERED ON A GET OPERATION.THE LENGTH FIELD OF A RECORD DESCRIPTOR WORD (RDW) FOR AVARIABLELENGTH RECORD SPECIFIES A VALUE LESS THAN 4. S002 - 08 - AN INVALID RECORD WAS ENCOUNTERED ON A PUT OR WRITEOPERATION. THE RECORD OR BLOCK LENGTH PLUS THE KEY LENGTHANDREQUIRED OVERHEAD ADD UP TO MORE THAN 32,767 BYTES. S002 - 0C - AN INVALID RECORD WAS ENCOUNTERED ON A PUT OR WRITEOPERATION. THE RECORD OR BLOCK LENGTH PLUS THE KEY LENGTHANDREQUIRED OVERHEAD IS GREATER THAN THE DASD TRACK CAPACITY.S002 - 10 - AN INVALID RECORD WAS ENCOUNTERED ON A PUT OPERATION;THE DATASET USES THE TRACK OVERFLOW FEATURE. THE RDW FOR AVARIABLE LENGTH RECORD SPECIFIES A LENGTH GREATER THAN32,752.S002 - 14 - AN INVALID RECORD WAS ENCOUNTERED ON A PUT OR WRITEOPERATION. THE RECORD LENGTH IS GREATER THAN THE BLOCKSIZESPECIFIED IN THE DCB. S002 - 18 - AN INVALID RECORD WAS ENCOUNTERED ON A PUT OPERATION;THE DATASET USES THE VARIABLE RECORD FORMAT. THE LENGTHVALUE OFTHE RDW IS EITHER: LESS THAN 4, GREATER THAN 32,767, GREATERTHANTHE BLOCKSIZE SPECIFIED IN THE DCB, OR LESS THAN 5 IF ASACONTROLCHARACTERS ARE BEING USED. S002 - 1C - THE ERROR OCCURRED DURING THE CREATION OF A DIRECT DATASET.A WRITE MACRO WAS ISSUED FOR A RECORD LARGER THAN THE TRACK CAPACITY, AND THE RECORD FORMAT DOES NOT USE THE TRACKOVERFLOWFEATURE. S002 - 20 - THE ERROR OCCURRED DURING THE CREATION OF A DIRECT DATASET.A WRITE MACRO WAS ISSUED CAUSING A SECONDARY EXTENT TO BE OBTAINED.THE BLOCK WILL NOT FIT ON THE AMOUNT OF SPACE ALLOCATED FORTHESECONDARY EXTENT. S002 - 24 - THE ERROR OCCURRED DURING THE CREATION OF A DIRECT DATASET.A WRITE MACRO WAS ISSUED TO WRITE OUT A BLOCK LARGER THAN THEPRIMARY EXTENT ON THE PREALLOCATED DATASET. THIS COULD ALSOOCCURIF ALLOCATION OF THE PRIMARY EXTENT WAS NON-CONTIGUOUS ANDANYOF THE SECONDARY EXTENTS WERE SMALLER THAN THE BLOCK. S002 - 28 - THE ERROR OCCURRED DURING THE CREATION OF A DIRECT DATASET.DURING THE EXECUTION OF OPEN IT WAS DETECTED THAT THEBLOCKSIZEWAS LARGER THAN THE PRIMARY EXTENT. S002 - 2C - THE ERROR OCCURRED WHILE OPENING AN ISAM DATASET.TOO MANY TRACKS WERE SPECIFIED FOR CYLINDER OVERFLOW. S002 - 30 - ONE OF THE FOLLOWING IS TRUE:- A READ WAS ISSUED BUT THE LENGTH TO BE READ WAS ZERO. - A QSAM PUT WITH MOVE MODE WAS ISSUED FOR RECFM=F, FB OR U BUT DCBLRECL CONTAINED A NON-POSITIVE VALUE. S002 - 34 - A READ MACRO WAS ISSUED FOR AN OUTPUT-ONLY DASD DATA SET.S002 - 3C - PDSE MEMBER CREATION WAS PREVENTED BECAUSE THE PDSEALREADY HAD THE MAXIMUM NUMBER OF MEMBERS (2**19 - 2). S002 - 50 - SERIALIZATION OF AN INTERNAL SAM CONTROL BLOCK (SACB)USED FOPR PROCESSING HAS BEEN VIOLATED. S002 - 54 - DEBCHK FAILURE DURING PDSE PROCESSING.S002 - 58 - AN INTERNAL SAM CONTROL BLOCK (SACB) USED FOR PROCESSINGPDSE REQUESTS IS INCORRECT. S002 - 5C - AN INTERNAL SAM CONTROL BLOCK (FRQ) USED FOR QUEUINGPDSE REQUESTS IS INCORRECT. S002 - 60 - NON-ZERO KEYLENGTH SPECIFIED FOR OUTPUT PDSE MEMBER.S002 - 64 - FOR BSAM, THE READ OR WRITE REQUEST COULD NOT BE ACCEPTEDBECAUSE THE VALUE OF NCP INT THE DCB HAD ALREADY BEEN REACHED.S002 - 68 - INCORRECT BLOCKSIZE SPECIFIED.S002 - 6C - UNABLE TO CREATE A PDSE MEMBER.S002 - 70 - UNABLE TO UPDATE AN INTERNAL SAM CONTROL BLOCK (PACB)USED FOR PDSE PROCESSING WITH INFORMATION CONCERNING THEMEMBERBEING ACCESSED. S002 - 74 - AN INTERNAL SAM CONTROL BLOCK (PACB) USED FOR STORINGPDSE DIRECTORY AND MEMBER INFORMATION IS INCORRECT. S002 - 78 - ERROR RETURN FROM IGWFMPCR WHEN ATTEMPTING TO GIVE CONTROLTO A ROUTINE TO PROCESS PDSE REQUESTS. S002 - 7C - POINT DETECTED THAT INFORMATION CONCERNING THE MEMBERBEING ACCESSED IS NOT FOUND IN THE PACB. S002 - 80 - POINT DETECTED AN ERROR WHILE ATTEMPTING TO SYNCHRONIZEDATA ON OUTPUT. S002 - 84 - POINT DETECTED AN ERROR WHILE ATTEMPTING TO RECONNECT TOA PDSE MEMBER FOR HOLD. S002 - 88 - POINT DETECTED AN ERROR WHILE ATTEMPTING TO RECONNECT TOA PDSE MEMBER FOR I/O. S002 - 8C - POINT DETECTED AN ERROR WHILE ATTEMPTING TO DISCONNECTFROM A PDSE MEMBER. S002 - 90 - POINT DETECTED AN ERROR WHILE ATTEMPTING TO CONNECT TOA PDSE MEMBER. S002 - 94 - INCORRECT ATTEMPT TO CREATE A PDSE MEMBER SINCE THEMAXIMUM NUMBER OF MEMBERS HAVE ALREADY BEEN CREATED. S002 - 98 - UNABLE TO COMPLETE A WRITE REQUEST ISSUED WITHIN APDSE MEMBER. S002 - 9C - INCORRECT UPDATE WRITE DETECTED. ALL OUTSTANDING READSHAD NOT BEEN CHECKED PRIOR TO THE WRITE. S002 - A0 - INCORRECT ATTEMPT TO ACCESS A PDSE DIRECTORY. EITHER:- WRITE ATTEMPTED TO THE DIRECTORY OF A PDSE. - READ ATTEMPTED TO THE DIRECTORY OF A PDSE AND EITHER THE RECFM WAS NOT F WITH BLKSIZE >= 256 ==OR== RECFM WAS NOT U WITH BLKSIZE >= 256. S002 - A4 - UNABLE TO COMPLETE THE READ AGAINST THE PDSE DIRECTORYDUE TO AN ERROR RETURN CODE FROM AN SMS SERVICE USED TO OBTAINDIRECTORY INFORMATION. S002 - A8 - MAXIMUM NUMBER OF RECORDS IN MEMBER HAS BEEN EXCEEDED.S002 - AC - BAD BUFFER FORMAT DETECTED FOR VARIABLE LENGTH RECORDS.EITHER: - RDW LENGTH IS LESS THAN 4. - LENGTH OF SPANNED RECORD IS GREATER THAN 32760. - THE SUM OF THE LENGTHS IN THE RDWS PLUS 4 DOES NOT EQUALTHELENGTH SPECIFIED IN THE BDW. - RECFM DOES NOT SPECIFY BLOCKED BUT MORE THAN 1 RDW IN BUFFER.S002 - B0 - EITHER RECFM=F AND DCBBLKSI DOES NOT EQUAL DCBLRECL,OR RECFM=FB AND DCBBLKSI IS NOT A MULTIPLE OF DCBLRECL. S003 - THE ERROR OCCURED DURING END-OF-BLOCK PROCESSING USING EITHERBSAM OR QSAM. THE ERROR OCURRED BECAUSE THE I/O MACROINSTRUCTIONS FOR A 3525-ASSOCIATED DATA SET WERE NOT EXECUTEDIN THE PROPER SEQUENCE.***IF THE REGISTER 15 RETURN CODE IS AVAILABLE, SUPPLY IT INTHE******S003 OPERAND FOR MORE SPECIFIC INFORMATION: H ABENDO(S003-RC)**S003 - 01 - THE ERROR WAS A READ SEQUENCE ERROR.S003 - 02 - THE ERROR WAS A PUNCH SEQUENCE ERROR.S003 - 03 - THE ERROR WAS A PRINT SEQUENCE ERROR.S004 - THE ERROR OCCURED DURING OPEN PROCESSING USING EITHER BSAMORQSAM BECAUSE A CONFLICTING OR INVALID DCB PARAMETER (FUNC ORRELATED PARAMETER) IS SPECIFIED.***IF THE REGISTER 15 RETURN CODE IS AVAILABLE, SUPPLY IT INTHE******S004 OPERAND FOR MORE SPECIFIC INFORMATION: H ABENDO(S004-RC)**S004 - 01 - INVALID DCB FUNC PARAMETER SPECIFIED.S004 - 02 - INVALID COMBINATION OF DCB FUNC PARAMETER AND CNTRL MACROSPECIFIED.S004 - 03 - CONFLICTING ACCESS METHODS SPECIFIED.S004 - 04 - INVALID DCB SPECIFIED FOR 3505 OR 3525.S004 - 05 - INVALID FORMAT CARD OR AN INVALID DEVICE SPECIFIED WITHOPTICAL MARK READ (OMR).S004 - 06 - DATA PROTECTION IMAGE NOT FOUND IN THE SYS1.IMAGELIBDATA SET, VOLUME CONTAINING SYS1.IMAGELIB NOT MOUNTED,OR SYS1.IMAGELIB NOT CATALOGED.S005 - THE ERROR OCCURRED BECAUSE OF AN INVALID DECB DURING READPROCESSING USING BSAM.***IF THE REGISTER 15 RETURN CODE IS AVAILABLE, SUPPLY IT INTHE******S005 OPERAND FOR MORE SPECIFIC INFORMATION: H ABENDO(S005-RC)**S005 - 04 - A REQUIRED ADDRESS WAS NOT SPECIFIED IN THE DECB. THISCAN BE EITHER THE HEADER ADDRESS AND/OR THE AREA ADDRESS.S005 - 08 - THE RBL TYPE OF READ WAS NOT USED FOR THE 3886.S006 - THE PROGRAM HAD AN INCORRECT AUTHORIZATION TO RUN A 1419.S008 - THE ERROR OCCURRED DURING EXECUTION OF A SYNAD ROUTINE. THEROUTINE WAS GIVEN CONTROL FOLLOWING EXECUTION OF A BSAM CHECKMACRO INSTRUCTION.S013 - CONFLICTING OR UNSUPPORTED PARAMETERS IN DCB; MEMBER NAMESPECIFIED IN DD NOT FOUND; NO DIRECTORY ALLOCATIONSUBPARAMETER IN DD.***IF THE REGISTER 15 RETURN CODE IS AVAILABLE, SUPPLY IT INTHE******S013 OPERAND FOR MORE SPECIFIC INFORMATION: H ABENDO(S013-RC)**--POSSIBLE CAUSE-- DCB PARAMETERS CONFLICT, NO BLKSIZE OR NOT VALID MULTIPLE OFLRECLMISSING OR MISPLACED SYSIN DD CARD PARTITIONED DATA SET MEMBER NOT FOUND MERGE - SORTIN01 DOES NOT CONTAIN THE MAXIMUM BLOCKSIZE JCL - TRIED TO CREATE A PDS WITHOUT ALLOCATING DIRECTORYBLOCKSS013 - 04 - AMERICAN NATIONAL STANDARD LABELS WERE SPECIFIED IN THELABEL PARAMETER OF THE DD STATEMENT, BUT ARE NOT SUPPORTEDBYTHE SYSTEM. CORRECT THE LABEL PARAMETER. - OPTCD=Q WAS SPECIFIED BUT IS NOT SUPPORTED BY THE SYSTEM.CORRECT THE DCB OPTCD OPTION. S013 - 08 - AMERICAN NATIONAL STANDARD LABELS WERE SPECIFIED IN THELABEL PARAMETER OF THE DD STATEMENT, BUT THE UNIT PARAMETERSPECIFIED A 7-TRACK TAPE DRIVE. ANSI LABELS A VALID ONLY FOR9-TRACK UNITS. S013 - 0C - A BUFFER LENGTH OF 0 WAS SPECIFIED FOR A BDAM DATASETFOR WHICH DYNAMIC BUFFERING WAS REQUESTED. S013 - 10 - AN OPEN MACRO WAS ISSUED FOR A NULL DATASET AND BLKSIZEAND BUFL ARE BOTH 0. SPECIFY ONE OR THE OTHER AS NON-ZERO.S013 - 14 - AN OPEN MACRO WAS ISSUED WITH OUTPUT OR OUTIN SPECIFIED.DCB SPECIFIES DSORG=PO, BUT THE DSCB INDICATES THE DATASETISNOT PARTITIONED. CHANGE DSORG TO PS, OR CREATE DATASET AS PDS.- AN OPEN MACRO WAS ISSUED WITH INPUT SPECIFIED. THE DSCBINDICATES THAT DSORG=PO, BUT THE DCB SPECIFIES NEITHERDSORG=PONOR PS. S013 - 18 - AN OPEN WAS ISSUED FOR A PARTITIONED DATASET. THESPECIFIED MEMBER NAME WAS NOT FOUND IN THE DATASET. S013 - 1C - AN OPEN MACRO WAS ISSUED FOR A PARTITIONED DATASET,BUT AN I/O ERROR WAS ENCOUNTERED SEARCHING THE DIRECTORY. S013 - 20 - AN OPEN MACRO WAS ISSUED FOR A SEQUENTIAL DATASET USINGTHE QUEUED ACCESS TECHNIQUE WITH RECFM=FB, BUT BLKSIZE IS NOTA MULTIPLE OF LRECL, OR FOR VARIABLE-LENGTH RECORDS, BLKSIZEIS NOT 4 BYTES GREATER THAN THE LRECL.S013 - 24 - AN OPEN WAS ISSUED WITH INPUT, INOUT, RDBACK, OR UPDATSPECIFIED, BUT THE DCB MACRF DID NOT SPECIFY EXCP, GET, ORREAD.S013 - 28 - AN OPEN MACRO WAS ISSUED WITH OUTPUT OR OUTIN SPECIFIED,BUT THE DCB DID NOT SPECIFY A MACRF OF EXCP, PUT, OR WRITE. S013 - 2C - A SEQUENTIAL DATASET USING THE QUEUED ACCESS TECHNIQUE WITHEXCHANGE BUFFERING WAS OPENED FOR INPUT, BUT THE BUFFERCONTROLBLOCK ADDRESS WAS 0. S013 - 30 - A SEQUENTIAL DATASET USING THE QUEUED ACCESS TECHNIQUE WITHEXCHANGE BUFFERING WAS OPENED FOR OUTPUT, BUT THE BUFFERCONTROLBLOCK ADDRESS (DCBBUFCB) WAS 0. S013 - 34 - ONE OF THE FOLLOWING WAS DETECTED:- AN OPEN MACRO WAS ISSUED FOR A DATASET WITH BLKSIZE AND BUFL EQUAL TO 0. THE SYSTEM DETERMINED THAT IT HAD TO OBTAINBUFFERS BUT WAS UNABLE TO DO SO. - RECFM WAS SPECIFIED WITH BOTH A AND M ATTRIBUTES. - QSAM, LRECL=0 AND RECFM WAS NOT V OR VB. - RECFM=V OR VB AND LRECL > (BLKSIZE-4). - QSAM AND BLKSIZE=0. - RECFM NOT VARIABLE OR UNDEFINED AND LRECL > BLKSIZE. - BFTEK=A,LRECL=0,RECFM=VBS. S013 - 38 - AN OPEN MACRO WAS ISSUED FOR A SEQUENTIAL DATASET ON ADIRECT ACCESS DEVICE WITH TRACK OVERFLOW, BUT THE BUFFER CONTROL BLOCK ADDRESS WAS ZERO. THIS TYPE OF ERROR OFTEN OCCURS IF A DCB IS SHARED BY TWO OR MORE TASKS, OR IS OPENED AND CLOSED SEVERAL TIMES WITHIN ONE JOB STEP. S013 - 3C - A SEQUENTIAL DATASET WAS OPENED FOR INPUT OR OUTPUT,BUT THE BUFFER CONTROL BLOCK ADDRESS WAS 0. THIS TYPE OFERROROFTEN OCCURS IF A DCB IS SHARED BY TWO OR MORE TASKS, OR IS OPENED AND CLOSED SEVERAL TIMES WITHIN ONE JOB STEP. S013 - 40 - A SEQUENTIAL OR DIRECT DATASET WAS OPENED FOR INPUT,BUT THE BUFFER CONTROL BLOCK ADDRESS WAS 0. S013 - 44 - AN OPEN MACRO WAS ISSUED FOR A DATASET ON A DIRECT ACCESSDEVICE FOR WHICH CHAINED SCHEDULING WAS SPECIFIED, BUT THEBUFFERCONTROL BLOCK ADDRESS WAS 0. S013 - 48 - AN OPEN MACRO WAS ISSUED FOR A SEQUENTIAL DATASET USING THEQUEUED ACCESS TECHNIQUE, BUT THE BUFFER CONTROL BLOCK ADDRESSWASZERO. S013 - 4C - AN OPEN MACRO WAS ISSUED FOR A SEQUENTIAL DATASET USING THEQUEUED ACCESS TECHNIQUE. THE SYSTEM DETERMINED THAT ABUFFERPOOL EXISTED FOR THIS DATASET AND MADE THE APPROPIATE TESTSHOWNBELOW WITH UNSATISFACTORY RESULTS: - IF THE DATA WAS TO BE SENT DIRECTLY TO A UNIT RECORD DEVICE(NOSPOOLING), THE BUFFER LENGTH VALUE IN THE BUFFER CONTROLBLOCKHAD TO BE EQUAL TO OR GREATER THAN THE VALUE SPECIFIED IN THEDCB FOR LOGICAL RECORD LENGTH (LRECL). - OTHERWISE, THE BUFFER LENGTH VALUE IN THE BUFFER CONTROLBLOCKHAD TO BE EQUAL TO OR GREATER THAN THE VALUE SPECIFIED IN THEDCB FOR BLKSIZE. S013 - 50 - AN OPEN MACRO ISSUED FOR A DATASET ALLOCATED TO A PRINTERDID NOT HAVE OUTPUT SPECIFIED AS AN OPEN OPTION. S013 - 54 - NO SECONDARY CONTROL UNIT COULD NOT BE FOUND FOR A 1419.S013 - 58 - AN OPEN MACRO WAS ISSUED FOR A PAPER TAPE DATASET ANDCONCATENATION WITH UNLIKE ATTRIBUTES WAS SPECIFIED. S013 - 5C - AN OPEN MACRO WAS ISSUED FOR A SEQUENTIAL DATASET USING THEQUEUED ACCESS TECHNIQUE. THE DATASET CONTAINED SPANNEDVARIABLELENGTH RECORDS LARGER THAN 32,756 BUT GET LOCATE MODE WAS NOTUSED.ALTERNATIVELY, BFTEK=A WAS SPECIFIED WITH MACRF=GM ORMACRF=PM.S013 - 60 - AN OPEN MACRO WAS ISSUED FOR A DATASET WITH A DCBSPECIFYING RECFM=F, AND BLKSIZE WAS NOT EQUAL TO LRECL. CORRECTTHE RECFM TO FB, OR MAKE LRECL AND BLKSIZE EQUAL. S013 - 64 - AN OPEN MACRO WAS ISSUED FOR A NULL DATASET USING ANACCESS METHOD OTHER THAN QSAM OR BSAM. THIS IS A NO-NO. S013 - 68 - AN OPEN WAS ISSUED FOR A DATASET WHOSE DCB SPECIFIEDBLKSIZE GREATER THAN 32,767, WHICH IS THE MAXIMUM ALLOWED. S013 - 6C - AN OPEN MACRO WAS ISSUED FOR A DATASET WITH RECFM=T IN THEDCB, REQUESTING TRACK OVERFLOW, BUT THE DIRECT ACCESS DEVICEDOES NOT SUPPORT TRACK OVERFLOW. S013 - 70 - AN OPEN MACRO WAS ISSUED FOR A DATASET ON MAGNETIC TAPE.A CONFLICT EXISTS AMONG LABEL PARAMETERS ON THE DD STATEMENT,AND DCBRECFM, DCBOPTCD, DCBBUFOF, AND DCBUSASI GIVE THE APPEARANCEOF MIXED USASI AND EBCDIC ATTRIBUTES TO THE DATASET; OROPTCD=QWAS SPECIFIED FOR A DATASET ON A DEVICE OTHER THAN MAGNETICTAPE.S013 - 74 - AN OPEN MACRO WAS ISSUED FOR AN OPTICAL CHARACTER READERDATASET, BUT THE OPEN OPTION DID NOT SPECIFY INPUT. S013 - 78 - AN OPEN MACRO WAS ISSUED FOR AN OPTICAL CHARACTER READERDATASET. THE BUFL PARAMETER IN THE DCB WAS SPECIFIED AS ZERO.S013 - 7C - AN OPEN MACRO WAS ISSUED FOR AN OPTICAL CHARACTER READERDATASET, BUT THE LRECL PARAMETER IN THE DCB WAS ZERO. S013 - 80 - AN OPEN MACRO WAS ISSUED FOR AN OPTICAL CHARACTER READERDATASET, BUT THE BUFL WAS LESS THAN THE LRECL. S013 - 84 - AN OPEN MACRO WAS ISSUED FOR AN OPTICAL CHARACTER READERDATASET. THE NUMBER OF BUFFERS SPECIFIED IN THE BUFFER POOLCONTROL BLOCK IS NOT THE SAME AS THAT SPECIFIED IN THE DCBBUFNO.S013 - 88 - AN OPEN MACRO WAS ISSUED FOR A TELECOMMUNICATIONS DEVICEBUT THE DCBDSORG DID NOT SPECIFY TSO. S013 - 8C - AN OPEN MACRO WAS ISSUED FOR A DIRECT ORGANIZATION DATASET(BDAM) BUT THE DCBRECFM PARAMETER WAS NOT SPECIFIED. S013 - A4 - A DCB WAS OPENED FOR A SYSIN OR SYSOUT DATASET BUT THEDSORG WAS NOT SPECIFIED AS PS. S013 - A8 - AN INVALID RECORD FORMAT WAS REQUESTED FOR A SYSIN ORSYSOUT DATASET. (RECFM=D, VS, OR VBS ARE INVALID FOR SYSIN)S013 - AC - A QSAM OPEN WAS ISSUED WITH A NON-ZERO KEYLENGTH IN THE DCBWHICH IS NOT SUPPORTED. (NOW SUPPORTED, BUT WITH INPUTONLY.)S013 - B0 - AN OPEN MACRO WAS ISSUED WITH THE RDBACK OPTION FOR A DCBSPECIFYING A RECORD FORMAT OF VARIABLE SPANNED RECORDS.THESEARE CONFLICTING PARAMETERS. S013 - B4 - AN OPEN MACRO WAS ISSUED WITH THE INOUT/OUTIN OPTION FORA DCB SPECIFYING THE QSAM MACRF VALUES; THESE ARE CONFLICTINGPARAMETERS. S013 - B8 - AN OPEN MACRO WAS ISSUED FOR THE 3890 DOCUMENT PROCESSORAND DCBHDR WAS NOT SPECIFIED IN THE DCB. S013 - BC - A SYSIN OR SYSOUT DCB WAS OPENED WITH INVALID OPTIONS.EITHER OPEN SPECIFIED UPDAT OR RDBACK, OR THE POINT MACRO FUNCTION WAS SPECIFIED IN MACRF=RP OR WP. REPOSITIONING OR UPDATING A SPOOLED DATASET IS NOT PERMITTED. S013 - C0 - A SYSIN OR SYSOUT DATASET COULD NOT BE OPENED BY A JOBENTRY SUBSYSTEM. THE FAILING DCB IS NOT OPENED, HOWEVER THETASKIS NOT TERMINATED. PROCESSING CONTINUES FOR OTHER DCBSOPENED.S013 - C4 - DURING THE CREATION OF A DIRECT DATASET, THE OPEN ROUTINEFOUND THAT THE DCB SPECIFIED READ(R) OR GET(G) IN THE MACRFFIELD.ONLY WRITE LOAD (WL) IS ALLOWED. S013 - C8 - THE OPEN SUBSYSTEM EXECUTOR MODULE WAS PASSED AN ERRORRETURN CODE IN REGISTER 15 AFTER ISSUING THE IEFSSREQ MACROTOCONNECT THE USER'S ACB TO THE SUBSYSTEM. THIS INDICATES THESUBSYSTEM WAS NOT OPERATING. S013 - CC - SETPRT PROCESSING FAILED TO SET UP THE DEVICE DURING ANOPEN FOR THE IBM 3800 PRINTING SUBSYSTEM. S013 - D0 - AN INVALID RECORD FORMAT OF FBS OR FS WAS SPECIFIED FOR APARTITIONED DATA SET. S013 - D0 - A DB/DBS RECORD FORMAT WAS SPECIFIED FOR QSAM LOCATE MODE,BUT THE LOGICAL RECORD INTERFACE IS NOT PRESENT IN THE ASSOCIATEDBUFFER CONTROL BLOCK; IE. SEGMENT MODE IS IMPLIED. S013 - D8 - A CONFLICT HAS OCCURRED FOR THE SPANNED RECORD FORMATEXTENDED LOGICAL RECORD INTERFACE (XLRI). BUFFER CONTROL BLOCK; IE. SEGMENT MODE IS IMPLIED. S013 - E4 - THE LIMIT OF 123 EXTENTS FOR A CONCATENATED PARTITIONEDDATA SET HAS BEEN EXCEEDED. (USED TO BE 256 EXTENTS?) S013 - E8 - THE OPEN VERIFICATION FUNCTION OF THE IEFSSREQ MACRORETURNED AN ERROR CODE IN REGISTER 15. S014 - 04 - (04 IS THE ONLY POSSIBLE RETURN CODE ASSOCIATED WITH S014)THE TASK WHICH ISSUED A CLOSE FOR A DASD DATA SET WAS NOT THE TASK WHICH OPENED THE DATA SET. S016 - AN ERROR OCCURRED IN SAM SIO/PAGE FIX OR DASD END-OF-BLOCKMODULES BECAUSE OF ONE OF THE FOLLOWING: - THE DASD END-OF-BLOCK MODULES ISSUED AN EXCPVR SVC REQUESTONBEHALF OF A USER REQUEST, BUT A PREVIOUS EXCPVR SVC REQUESTHAD NOT COMPLETED. ONE OF THE FOLLOWINF OCCURRED: - A DATA EXTENT CONTROL BLOCK (DECB) WAS USED TWICE. - MULTIPLE READS OR WRITES WERE ISSUED, BUT ONLY THE LAST READ OR WRITE WAS CHECKED.- AN EXCPVR SVC REQUEST ON BEHALF OF A USER REQUEST WAS GOINGTOBE ISSUED TO READ A DATA SET THAT IS EXECUTE ACCESS PROTECTED,BUT THE USER IS NOT IN SUPERVISOR STATE. (THE SAM SIO APPENDAGE ISSUED THIS ABEND.) S020 - DURING AN OPEN FOR A BDAM DATA SET THE CONTROL PROGRAM FOUNDTHAT DCBMACRF DID NOT CONTAIN AN A, K OR I (RC=04), OR THEBDAMDATA SET CONTAINED ZERO EXTENTS (RC=08).S021 - A CALLER OF THE ASCBCHAP ROUTINE PASSED TO ASCBCHAP AN ASCBADDRESS THAT HAD BITS SET TO ONE IN ITS HIGH ORDER BYTE. S022 - THE VPSS ENCOUNTERED A MISSING DEVICE END ON CONTROL PORT 0.S023 - LNKLST LOOKASIDE (LLA) COULD NOT OBTAIN ALL THE LNKLSTDIRECTORY ENTRIES. S024 - AN ABNORMAL TERMINATION OCCURRED IN PRINT SERVICES FACILITY.S027 - AN ABNORMAL TERMINATION OCCURRED IN PRINT SERVICES FACILITY.S028 - A PAGING OPERATION HAS NOT COMPLETED SUCCESSFULLY DUE TO ONEOF THE FOLLOWING: - A PERMANENT I/O ERROR OCCURRED WHILE ATTEMPTING A PAGE-INORSWAP-IN OPERATION. THE DATA BEING PAGED IN OR SWAPPED IN ISLOST.- A REAL STORAGE MANAGEMENT ROUTINE OR ANOTHER SYSTEM ROUTINEPERFORMING A SERVICE FOR RSM SUFFERED AN INTERMEDIATE ERROR.THE FUNCTION PERFORMED IS TERMINATED.- A AUXILIARY STORAGE MANAGEMENT ROUTINE SUFFERED ATRANSLATIONERROR WHILE USING THE CONTROL REGISTER OF ANOTHER ADDRESSSPACETO UPDATE THAT ADDRESS SPACE'S LSQA.S029 - AN INVALID VIO REQUEST WAS DETECTED BY THE PAGE OPERATIONSSTARTER ROUTINE OF ASM. THE SYS1.LOGREC ERROR RECORDCONTAINSA HEXADECIMAL REASON CODE. S02A - JES2 FOUND THAT DATA MANAGEMENT CONTROL BLOCKS OR THE JES2UBUF CONTROL BLOCK WAS NO LONGER VALID DURING EXECUTION OFA DATAMANAGEMENT REQUEST FOR A SPOOL DATA SET. S02B - A USER EXIT ROUTINE ISSUED A RETURN CODE GREATER THAN THATSPECIFIED IN THE &MAXRC PARAMETER OF THE $EXIT### MACRO. S02C - AN ERROR OCCURRED IN JES2 SUPPORT OF AN FSS ADDRESS SPACE.S02D - THE JES2 MAIN TASK WAS ABENDED BY THE OPERATOR OR ACATASTROPHIC ERROR. S030 - DURING A BISAM OR QISAM OPEN DCBMACRF DID NOT INDICATE AVALID MODE OF OPERATION. S031 - A QISAM I/O ERROR OCCURRED.S032 - DURING A BISAM OR QISAM OPEN DCBMACRF WAS NOT VALID FOR ISAM.S03B - ISAM DATASET TO BE PROCESSED, BUT NOT CREATED OR ITS DCBNOT CLOSED AFTER CREATION.--POSSIBLE CUASE-- DATASET WAS TO BE WRITTEN ON BUT WAS OPENED AS INPUT LRECL/BLKSIZE PROBLEM EXISTS - INVALID VALUES OR NOTMULTIPLESS03D - THE ERROR OCCURRED DURING THE EXECUTION OF A QISAM OR BISAMORBDAM MACRO INSTRUCTION. ***IF THE REGISTER 15 RETURN CODE IS AVAILABLE, SUPPLY IT INTHE******S03D OPERAND FOR MORE SPECIFIC INFORMATION: H ABENDO(S03D-RC)**S03D - 04 - AN OPEN MACRO WAS ISSUED FOR AN INDEXED SEQUENTIAL ORDIRECT DATASET. THE VOLUME SERIAL NUMBERS ON THE DDSTATEMENTWERE NOT SPECIFIED IN THE SAME ORDER THAT THE DATASET WAS CREATED.S03D - 08 - AN OPEN MACRO WAS ISSUED FOR AN INDEXED SEQUENTIAL DATASET.THE FIRST VOLUME OF THE DATASET DOE NOT HAVE A FORMAT2 DSCB.S03D - 0C - AN OPEN MACRO WAS ISSUED FOR A DIRECT DATASET. THE DATASETHAS AN INDEXED SEQUENTIAL ORGANIZATION. S047 - AN UNAUTHORIZED PROGRAM REQUESTED A RESTRICTED SVC.S04B - AN INVALID OPERATION CODE WAS PASSED TO A TSO LINKAGE ASSISTROUTINE (LAR). ***IF THE REGISTER 15 RETURN CODE IS AVAILABLE, SUPPLY IT INTHE******S04B OPERAND FOR MORE SPECIFIC INFORMATION: H ABENDO(S04B-RC)**S04B - 04 - THE LAR (IKJEFTSL) FOR THE TERMINAL MONITOR PROGRAM (TMP)RECEIVED AN INVALID FUNCTION NUMBER. S04B - 08 - THE SERVICE ROUTINE'S LAR (IKJTSLAR) WAS INVOKED ATIKJTSLAR, WHICH IS AN INVALID SERVICE ROUTINE ENTRY POINT. S04C - THE TERMINAL MONITOR PROGRAM (TMP) WAS INVOKED AT ENTRY POINTIKJEFT1A AND THE TMP DETACHED A PROGRAM THAT COMPLETED WITH A NON-ZERO COMPLETION CODE (WHICH IS IN REGISTER 15). S04E - INTERNAL IBM DATABASE 2 (DB2) ERROR.S04F - DB2 ABNORMAL TERMINATION TO AVOID DATA INTEGRITY PROBLEMS.S052 - A PROGRAM MADE AN INVALID PC/AUTH REQUEST. CHECK THE CODEINREGISTER 15. S053 - A PROGRAM MADE A PC/AUTH REQUEST BUT AN ERROR PREVENTEDNORMAL COMPLETION. CHECK THE CODE IN REGISTER 15. S064 - AN ADDRESS SPACE THAT HOLDS A CROSS MEMORY LOCAL LOCK (CMLLOCK) TERMINATED ABNORMALLY BEFORE IT FREED THE LOCK. S071 - THE OPERATOR PRESSED THE RESTART KEY TO ACTIVATE THE SYSTEM'SRECOVERY AND TERMINATION PROCESS. THE PROGRAM RUNNING ATTHETIME THE OPERATOR PRESSED THE RESTART BUTTON WAS SENT THROUGHABEND PROCESSING BECAUSE THE OPERATOR DETERMINED IT WAS INANONCANCELABLE LOOP OR WAIT STATE. S078 - RCT (REGION CONTROL TASK) PROCESSING HAS RECEIVED ANUNACCEPTABLE RETURN CODE FROM AN INVOKED ROUTINE AND CANNOT CONTINUE PROCESSING. RCT RECOVERY RECORDS THE ERROR IN SYS1.LOGREC, PERFORMS RESOURCE CLEAN-UP, REQUESTS ASYS1.DUMP OFTHE ADDRESS SPACE AND THEN REQUESTS ADDRESS TERMINATION. S079 - RCT (REGION CONTROL TASK) ATTENTION EXIT PROCESSING HASRECEIVED AN UNACCEPTABLE RETURN CODE FROM AN INVOKED ROUTINEANDCANNOT CONTINUE PROCESSING. RCT RECOVERY RECORDS THE ERRORINSYS1.LOGREC, PERFORMS RESOURCE CLEAN-UP, REQUESTS ASYS1.DUMP OFTHE ADDRESS SPACE AND THEN REQUESTS ADDRESS TERMINATION. S07C - SUPERVISOR CONTROL RECOVERY HAS DETECTED AN ERROR WHICHREQUIRES THAT THE CURRENT TASK BE TERMINATED OR THAT THECURRENTADDRESS SPACE BE TERMINATED. S07F - DURING RECOVERY, VERIFICATION OF THE TCB QUEUE ASSOCIATEDWITHTHE TERMINATED ADDRESS SPACE RESULTED IN AN EMPTY TCB QUEUE.THE ADDRESS SPACE OR JOB IS TERMINATED. RESUBMIT THE JOB. S0A7 - DURING Z NET,CANCEL COMMAND PROCESSING, VTAM FOUND THAT A USERHAD NOT SPECIFIED A TPEND EXIT ROUTINE, OR VTAM COULD NOT SCHEDULEA USER'S TPEXIT ROUTINE. S0A8 - VTAM DETECTED AN ERROR DURING EXECUTION OF AN APPLICATIONPROGRAM. THE TWO LOW-ORDER BYTES OF REGISTER 15 CONTAIN A HEXADECIMAL REASON CODE. 2101--A VTAM VALIDITY CHECK OF THE USER'S RPL FAILED BECAUSETHE RPL DOES NOT HAVE THE SAM PROTECTION KEY AS THEAPPLICATION PROGRAM'S TCB.7001--THE USER'S RPL OR ECB IS INVALID.S0A9 - EITHER A HALT NET,CANCEL COMMAND WAS ENTERED OR AN ERROROCCURRED DURING EXECUTION OF A VTAM MODULE. THE TWO LOW-ORDER BYTES OF REGISTER-15 CONTAIN A HEXIDECIMAL REASON CODE. 0000--A HALT NET,CANCEL COMMAND HAS BEEN PROCESSED.10F1--THE ACF/VTAM STAE RETRY ROUTINE ISSUED AN ABEND0A9 IN ORDER TO GIVE CONTROL TO THE USER RECOVERYROUTINE (STAE EXIT ROUTINE).3100--THERE ARE NOT ENOUGH I/O BUFFERS TO SATISFY AVTAM STORAGE REQUEST.3111--A VTAM MODULE FINISHED PROCESSING BEFORE ITRELEASED A LOCK.3141--A VTAM DESTINATION VECTOR TABLE (DVT) ENTRYIS INVALID FOR THE DEFINED ATTACHMENT.7002--A VTAM REQUEST FOR STORAGE FAILED7003--A VTAM REQUEST TO RELEASE STORAGE FAILED BECAUSETHE STORAGE HAD ALREADY BEEN RELEASED.7004--VTAM COULD NOT OBTAIN A LOCAL MEMORY LOCK.7009--VTAM WAS UNABLE TO RESTORE ITS REGISTERS AFTER AUSER EXIT ROUTINE RETURNED CONTROL TO VTAM.7071--A RELSTORE WAS ISSUED FOR A PREVIOSLY FREED BUFFER.7141--CONTROL CANNOT BE PASSED TO THE PROPER VTAM MODULE.EITHER A VTAM DESTINATION VECTOR TABLE ENTRY IS INVALIDFOR THE DEFINED ATTACHMENT OR VTAM STOARGE HAS BEEN ALTERED.S0AA - AN ABEND CONDITION OCCURRED DURING EXECUTION OF VTAM.THE ERROR COULD NOT BE ASSOCIATED WITH ANY PARTICULAR TCB.ALL TASKS IN THE ADDRESS SPACE ARE ABNORMALLY TERMINATED.S0AE - IOS SUPPORT OF SYSTEM RESTART PROCESSING FOUND THAT THE I/OPURGE MODULE (IGC0001F) WAITING FOR THE COMPLETION OF AN I/OREQUEST. THE SYSTEM ABNORMALLY TERMINATES ALL TASKS IN THEADDRESS SPACE, THEN THE SYSTEM TERMINATES THE ADDRESS SPACE.S0B0 - AN UNCORRECTABLE ERROR WAS DETECTED BY THE SWA MANAGER.***IF THE REGISTER 15 RETURN CODE IS AVAILABLE, SUPPLY IT INTHE******S0B0 OPERAND FOR MORE SPECIFIC INFORMATION: H ABENDO(S0B0-RC)**S0B0 - 04 - INVALID FUNCTION REQUESTED.S0B0 - 08 - INVALID SVA (DOES NOT POINT TO THE BEGINNING OF A SWAPREFIX OR THE SWA PREFIX HAS BEEN DESTROYED). S0B0 - 0C - ATTEMPTING TO READ A BLOCK NOT YET WRITTEN.S0B0 - 10 - INVALID LENGTH (0 OR NEGATIVE FOR ASSIGN LOCATE ORATTEMPTING TO READ OR WRITE A RECORD, WHICH IS NOT 176 BYTES,INMOVE MODE). S0B0 - 14 - INVALID COUNT FIELD (0 FOR READ, WRITE, ASSIGN OR 00 FORWRITE AND ASSIGN). S0B0 - 18 - QMNGRIO MACRO WAS ISSUED WITH BOTH OR NEITHER OF THE READAND WRITE BITS SET. S0B0 - 1C - INVALID ID (THE CALLER ATTEMPTED TO WRITE A BLOCK FOR THEFIRST TIME AND HAS EITHER PASSED A NON-EXISTING ID OR HASFAILEDTO PASS ONE AND THE BLOCK DOES NOT HAVE AN IMBEDDED ID).。

chapter_6_THE_SYSTEM_UNIT

6-11
Memory
Holding area for data, instructions, and information Types of memory chips
RAM – holds programs and data
ROM – fixed start-up instructions CMOS – flexible start-up instructions
6
THE SYSTEM UNIT
6-2
Competencies
Describe the four basic types of system units Discuss how a computer uses binary codes Describe the major system unit components Describe system boards, microprocessors, and memory Describe the function of the system clock, expansion slots, boards, and bus lines Discuss ports, cables, and power supply
Measured as bus width More lanes, faster traffic
Two basic categories
System buses Expansion buses
6-17
Types of Expansion Buses
Industry Standard Architecture (ISA) Peripheral Component Interconnect (PCI) Advanced Graphic Port (AGP) Universal serial bus (USB) FireWire buses

JavaCRC校验

import java.io.IOException;public class CRC16Checker {private static int[] index = new int[] { 16, 15, 2, 0 };private static int[] getBinary(String text) {StringBuffer num = new StringBuffer();String s; char ch;for (int i = 0; i < text.length(); i++) { // Change each char to binary code.s = Integer.toBinaryString(text.charAt(i));// If the code is less than 8 bit, make it as 8 bit.for (int j = 8 - s.length(); j > 0; j--) num.append(0);num.append(s);}int len = num.length();int[] code = new int[len];for (int i = 0; i < len; i++) // Change each 0/1 char to int.code[i] = Character.getNumericValue(num.charAt(i));return code;}private static String toHex(int[] num) {StringBuffer hex = new StringBuffer(num.length / 4);char[] ch = new char[4];for (int i = 0; i < num.length;) {// Change each 0/1 int to char.ch[0] = Character.forDigit(num[i++], 2);ch[1] = Character.forDigit(num[i++], 2);ch[2] = Character.forDigit(num[i++], 2);ch[3] = Character.forDigit(num[i++], 2);// Change each 4-bit-code to hex number.hex.append(Integer.toHexString(Integer.parseInt(String.valueOf(ch), 2)));}return hex.toString();}// CRC codes main processpublic static int[] makeCRCCodes(int[] sourceCodes, int[] multinomial) {// The lenght of CRC code is N bits longer than source code. The codes// from 0 to sourceLength are same as the source. N bits aftersource// are the CRC codes. N is decided by the multinomial.// CRC码数组总长为原码长加上校验码码长。

二进制输入RS编码中英文翻译

Binary-Input RS EncoderThe Binary-Input RS Encoder block creates a Reed-Solomon code with message length K and codeword length N. You specify both N and K directly in the dialog box. The symbols for the code are binary sequences of length M, corresponding to elements of the Galois field GF(2M), where the first bit in each sequence is the most significant bit. Restrictions on M and N are given in the section Restrictions on the M and the Codeword Length N below. The difference N-K must be an even integer. The input and output are binary-valued signals that represent messages and codewords, respectively. The input must be a frame-based column vector whose length is an integer multiple of M*K. For more information on representing data for Reed-Solomon codes, see the section Integer Format (Reed-Solomon only)." The default value of M is the smallest integer that is greater than or equal to log2(N+1), that is, ceil(log2(N+1)). If N is less than 2M-1, the block uses a shortened Reed-Solomon code. Each M*K input bits represent K integers between 0 and 2M-1. Similarly, each M*N output bits represent N integers between 0 and 2M-1. These integers in turn represent elements of the Galois field GF(2M). An (N,K) Reed-Solomon code can correct up to floor((N-K)/2) symbol errors (not bit errors) in each codeword.Specifying the Primitive PolynomialYou can specify the primitive polynomial that defines the finite field GF(2M), corresponding to the integers that form messages and codewords. To do so, first select the box next to Specify primitive polynomial. Then, in the Primitive polynomial field, enter a binary row vector that represents a primitive polynomial over GF(2) of degree M, in descending order of powers. For example, to specify the polynomial ,enter the vector [1 0 1 1]. If you do not select the box next to Specify primitive polynomial, the block uses the default primitive polynomial of degree M = ceil(log2(N+1)). You can display the default polynomial by entering primpoly(ceil(log2(N+1))) at the MATLAB prompt.Restrictions on the M and the Codeword Length N The restrictions on the degree M of the primitive polynomial and the codeword length N are as follows:If you do not select the box next to Specify primitive polynomial, N must lie inthe rangemust lie in the range .If you do select the box next to Specify primitive polynomial, N must lie in therange and M must lie in the range .Specifying the Generator PolynomialYou can specify the generator polynomial for the Reed-Solomon code. To do so, first select the box next to Specify generator polynomial. Then, in the Generator polynomial field, enter an integer row vectorwhose entries are between 0 and 2M-1. The vector represents a polynomial, in descending order of powers, whose coefficients are elements of GF(2M) represented in integer format. See the section Integer Format (Reed-Solomon only) for more information about integer format. The generator polynomial must be equal to a polynomial with a factored form, where a is the primitive element of the Galois field over which the input message is defined, and b is a non-negative integer. If you do not select the box next to Specify generator polynomial, the block uses the default generator polynomial, corresponding to b=1, for Reed-Solomon encoding. You can display the default generator polynomial by typing rsgenpoly(N1,K1), where N1=2^M-1 and K1=K+(N1-N), at the MATLAB prompt, if you are using the default primitive polynomial. If the Specify primitive polynomial box is selected, and you specify the primitive polynomial specified as poly, the default generator polynomial is rsgenpoly(N1,K1,poly).Binary-Output RS DecoderThe Binary-Output RS Decoder block recovers a binary message vector from a binary Reed-Solomon codeword vector. For proper decoding, the parameter values in this block should match those in the corresponding Binary-Input RS Encoder block. The Reed-Solomon code has message length K and codeword length N. You specify both N and K directly in the dialog box. The symbols for the code are binary sequences of length M, corresponding to elements of the Galois field GF(2M), where the first bit in each sequence is the most significant bit. Restrictions on M and N are described in the section Restrictions on the M and the Codeword Length N. The difference N-K must be an even integer. The input and output are binary-valued signals that represent messages and codewords, respectively. The input must be a frame-based column vector whose length is an integer multiple of M*K. The output is a frame-based column vector whose length is the same integer multiple of M*N. For more information on representing data for Reed-Solomon codes, see the section Integer Format (Reed-Solomon only)." The default value of M is ceil(log2(N+1)), that is, the smallest integer greater than or equal to log2(N+1). You can change the value of M from the default by specifying the primitive polynomial for GF(2M), as described in the section Specifying the Primitive Polynomial below. If N is less than 2M-1, the block uses a shortened Reed-Solomon code. You can also specify the generator polynomial for the Reed-Solomon code, as described in the section Specifying the Generator Polynomial. Each M*K input bits represent K integers between 0 and 2M-1. Similarly, each M*N output bits represent N integers between 0 and 2M-1. These integers in turn represent elements of the Galois field GF(2M). The second output is a vector of the number of errors detected during decoding of the codeword. A -1 indicates that the block detected more errors than it could correct using the coding scheme. An (N,K) Reed-Solomon code can correct up to floor((N-K)/2) symbol errors (not bit errors) in each codeword. You can disable thesecond output by clearing the box next to Output port for number of corrected errors. This removes the block's second output port.Integer-Input RS EncoderThe Integer-Input RS Encoder block creates a Reed-Solomon code with message length K and codeword length N. You specify both N and K directly in the block dialog. The symbols for the code are integers between 0 and 2M-1, which represent elements of the finite field GF(2M). Restrictions on M and N are described in the section Restrictions on M and the Codeword Length N below. The difference N - K must be an even integer. The input and output are integer-valued signals that represent messages and codewords, respectively. The input must be a frame-based column vector whose length is an integer multiple of K. The output is a frame-based column vector whose length is the same integer multiple of N. For more information on representing data for Reed-Solomon codes, see the section Integer Format(Reed-Solomon only)." The default value of M is the smallest integer that is greater than or equal to log2(N+1), that is, ceil(log2(N+1)). You can change the value of M from the default by specifying the primitive polynomial for GF(2M), as described in the section Specifying the Primitive Polynomial following. If N is less than 2M-1, the block uses a shortened Reed-Solomon code. An (N, K) Reed-Solomon code can correct up to floor((N-K)/2) symbol errors (not bit errors) in each codeword.Specifying the Primitive PolynomialYou can specify the primitive polynomial that defines the finite field GF(2M), corresponding to the integers that form messages and codewords. To do so, first check the box next to Specify primitive polynomial. Then, in the Primitive polynomial field, enter a binary row vector that represents a primitive polynomial over GF(2) of degreeM, in descending order of powers. For example, to specify the polynomial, enter the vector [1 0 1 1].If you do not select the box next to Specify primitive polynomial, the block uses the default primitive polynomial of degree M = ceil(log2(N+1)). You can display the default polynomial by entering primpoly(ceil(log2(N+1))) at the MATLAB prompt.Restrictions on M and the Codeword Length N The restrictions on the degree M of the primitive polynomial and the codeword length N are as follows:If you do not select the box next to Specify primitive polynomial, N must lie inthe rangeIf you do select the box next to Specify primitive polynomial, N must lie in therange and M must lie in the rangeSpecifying the Generator PolynomialYou can specify the generator polynomial for the Reed-Solomon code. To do so, first select the box next to Specify generator polynomial. Then, in the Generator polynomial field, enter an integer row vector whose entries are between 0 and 2M-1. The vector represents a polynomial, in descending order of powers, whose coefficients are elements of GF(2M) represented in integer format. See the section Integer Format (Reed-Solomon only) for more information about integer format. The generator polynomial must be equal to a polynomial with a factored formwhere a is the primitive element of the Galois field over which the input message is defined, and b is an integer. If you do not select the box next to Specify generator polynomial, the block uses the default generator polynomial, corresponding to b=1, for Reed-Solomon encoding. You can display the default generator polynomial by typing rsgenpoly(N1,K1), where N1 = 2^M-1 and K1 = K+(N1-N), at the MATLAB prompt, if you are using the default primitive polynomial. If the Specify primitive polynomial box is selected, and you specify the primitive polynomial specified as poly, the default generator polynomial is rsgenpoly(N1,K1,poly).Integer-Output RS DecoderThe Integer-Output RS Decoder block recovers a message vector from aReed-Solomon codeword vector. For proper decoding, the parameter values in this block should match those in the corresponding Integer-Input RS Encoder block.The Reed-Solomon code has message length K and codeword length N. You specify both N and K directly in the block dialog. The symbols for the code are integers between 0 and 2M-1, which represent elements of the finite field GF(2M). Restrictions on M and N are described in the section Restrictions on M and the Codeword Length N following. The difference N - K must be an even integer.The input and output are integer-valued signals that represent messages and codewords, respectively. The input must be a frame-based column vector whose length is an integer multiple of K. The output is a frame-based column vector whose length is the same integer multiple of N. For more information on representing data for Reed-Solomon codes, see the section Integer Format (Reed-Solomon only)."The default value of M is ceil(log2(N+1)), that is, the smallest integer greater than or equal to log2(N+1). You can change the value of M from the default by specifying the primitive polynomial for GF(2M), as described in the section Specifying the Primitive Polynomial below. If N is less than 2M-1, the block uses a shortened Reed-Solomon code.You can also specify the generator polynomial for the Reed-Solomon code, as described in the section Specifying the Generator Polynomial.An (N, K) Reed-Solomon code can correct up to floor((N-K)/2) symbol errors (not bit errors) in each codeword.The second output is the number of errors detected during decoding of the codeword. A -1 indicates that the block detected more errors than it could correct using the coding scheme. An (N,K) Reed-Solomon code can correct up tofloor((N-K)/2) symbol errors (not bit errors) in each codeword.You can disable the second output by clearing the box next to Output number of corrected errors. This removes the block's second output port.The sample times of the input and output signals are equal.二进制输入RS编码二进制输入的RS编码器的结构创建一个消息长度为k和码字长度n的Reed - Solomon码。

数据通信原理实验指导书

实验一编码与译码一、实验学时：2学时二、实验类型：验证型三、实验仪器：安装Matlab软件的PC机一台四、实验目的：用MATLAB仿真技术实现信源编译码、过失操纵编译码,并计算误码率。

在那个实验中咱们将观看到二进制信息是如何进行编码的。

咱们将要紧了解：1．目前用于数字通信的基带码型2．过失操纵编译码五、实验内容：1．经常使用基带码型（1）利用MATLAB 函数wave_gen 来产生代表二进制序列的波形,函数wave_gen 的格式是：wave_gen(二进制码元,‘码型’,Rb)此处Rb 是二进制码元速度,单位为比特/秒（bps）。

产生如下的二进制序列：>> b = [1 0 1 0 1 1];利用Rb=1000bps 的单极性不归零码产生代表b的波形且显示波形x，填写图1-1：>> x = wave_gen(b,‘unipolar_nrz’,1000);>> waveplot(x)（2）用如下码型重复步骤（1）（提示：能够键入“help wave_gen”来获取帮忙），并做出相应的记录：a 双极性不归零码b 单极性归零码c 双极性归零码d 曼彻斯特码(manchester)x 10-3x 10-3图1-1 单极性不归零码图1-2双极性不归零码x 10-3x 10-32．过失操纵编译码（1）利用MATLAB 函数encode 来对二进制序列进行过失操纵编码, 函数encode 的格式是：A ．code = encode(msg,n,k,'linear/fmt',genmat)B ．code = encode(msg,n,k,'cyclic/fmt',genpoly)C ．code = encode(msg,n,k,'hamming/fmt',prim_poly)其中A ．用于产生线性分组码，B ．用于产生循环码，C ．用于产生hamming 码，msg 为待编码二进制序列，n 为码字长度，k 为分组msg 长度，genmat 为生成矩阵，维数为k*n ，genpoly 为生成多项式,缺省情形下为cyclpoly(n,k)。

格雷码（GrayCode）转二进制码（BinaryCode）

格雷码（GrayCode）转⼆进制码（BinaryCode）学习verilog generate语句时，偶然看到⽤generate语句来进⾏格雷码到⼆进制码转换的代码，就从⽹上找了⼀些案例来学习。

下表为⼏种⾃然⼆进制码与格雷码的对照表：⼗进制数⾃然⼆进制数格雷码⼗进制数⾃然⼆进制数格雷码0000000008100011001000100019100111012001000111010101111300110010111011111040100011012110010105010101111311011011601100*************7011101001511111000格雷码转换为⼆进制码算法有以下⼏种表述形式：表述⼀：⼆进制格雷码为G n-1G n-2...G2G1G0对应的⾃然⼆进制码为B n-1B n-2...B2B1B0其中：最⾼位保留—B n-1=G n-1其他各位—B i-1=G i-1xor B i，i=1,2,...,n-1表述⼆：B i = ˆG[n-1:i]=G[n-1]ˆG[n-2]ˆ..ˆG[i]，i=0,1,...,n-1表述三：B i = ˆ(G>>i)，i=0,1,...,n-1表述⼀的仿真实例：源代码：1///adamite/archive/2008/10/20/1314949.html2//example23module GrayToBinary2 (binarycode, graycode);4parameter n = 4; // this module is parameterizable5output reg [n-1:0] binarycode;6input [n-1:0] graycode;7integer i;8always @ (graycode)9begin10 binarycode[n-1]=graycode[n-1];11for(i=1;i<=n-1;i=i+1)12 binarycode[i-1]=graycode[i-1] ^ binarycode[i];//⽐较节省空间13end14endmodule测试代码：1 `timescale 1ns/1ns2module tb_GrayToBinary2;34reg [3:0] gray;5wire [3:0] bin;67 GrayToBinary2 dut (bin,gray);813 #10;14 gray = 4'h2;15 #10;16 gray = 4'h3;17 #10;18 gray = 4'he;19 #10;20 gray = 4'h7;21 #10;22 gray = 4'hf;23end24endmodule仿真结果：modelsim⽣成的原理图（注意要在vsim后⾯加上-debugDB选项）从仿真结果来看，格雷码转⼆进制码过程中出现错误。

中的二进制编码

中的二进制编码
在计算机科学中，二进制编码（Binary Encoding）是一种将数据转换为二
进制形式的方法。

它通常用于数据存储、传输和处理。

以下是一些常见的二进制编码方式：
1. ASCII码：ASCII码是使用7位二进制位表示字符的编码方式。

它可以表示128个不同的字符，包括英文字母、数字、标点符号等。

2. UTF-8编码：UTF-8是一种变长字符编码，使用1到4个字节表示字符。

它可以表示世界上几乎所有语言的字符。

3. 二进制补码：在计算机中，整数通常使用二进制补码表示。

这种方式利用了负数的二进制表示和正数的二进制表示之间存在一种互补关系，从而简化了加法和减法运算的实现。

4. 十六进制编码：十六进制编码使用4位二进制位表示一个数字，可以表示0到15之间的整数。

十六进制编码常用于表示计算机中的地址和内存地址。

这些编码方式都有自己的特性和用途，选择合适的编码方式可以大大提高数据处理的效率和准确性。

二进制代码

• 该特点常用于模拟量的转换。当模拟量发生微小变化，格雷码仅仅改变一位，这与其它码同时改变2 位或更多的情况相比，更加可靠,且容易检错。
二进制码 b3b2b1b0
0000 0001 0010 0011 0100 0101 0110 0111 1000 1001 1010 1011 1100 1101 1110 1111
余３码的特点:当两个十进制的和是10时，相应的二进制正好是16，于是可自动产生进位信号,而不需修正.0和9, 1和8,…..6和4 的余３码互为反码,这对在求对于10的补码很方便。
余3码循环码：相邻的两个代码之间仅一位的状态不同。按余3 码循环码组成计数器时，每次转换过程只有一个触发器翻转，译码时不会发生竞争－冒险现象。
0100
0100
0111
0100
5
0101
1011
1000
1000
1100
6
0110
1100
1001
1001
1101
7
0111
1101
1010
1010
1111
8
1000
1110
1011
1011
1110
9
1001
1111
1100
1100
1010
（2）各种编码的特点
有权码：编码与所表示的十进制数之间的转算容易如(10010000) 8421BCD=(90)Ｄ
的键盘指令输入和数据等。
1.4.1二-十进制码
（1）几种常用的BCD代码
BCD码十进制数码
8421码
2421 码 5421 码
余3码
余3循
环码
0
0000