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MATLAB信号处理超级学习手册

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MATLAB信号处理超级学习手册

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MATLAB凭借其数值计算与图形可视化功能的完美结合，在数字信号处理领域得到了广泛的应用。《MATLAB信号处理超级学习手册》以MATLAB R2013a版本为基础，系统地讨论了数字信号处理的基本理论、基本分析方法、基本算法和设计方法，涉及了数字信号处理的各个方面，是一本比较全面的信号处理参考书。
《MATLAB信号处理超级学习手册》共分为12章，全面系统地阐述了数字信号处理的相关知识，其中前9章包括MATLAB基础入门、离散时间信号及系统的介绍、Z变换、傅里叶变换、IIR滤波器设计、FIR滤波器设计、自适应滤波器设计、小波分析、随机信号处理等，后3章则介绍了时频分析、高阶谱分析以及MATLAB的一些简单应用。
《MATLAB信号处理超级学习手册》的特点是内容全面丰富，叙述深入浅出，在讲解上述内容的同时，给出了大量简单而实用的例子。《MATLAB信号处理超级学习手册》既可作为电子工程、计算机工程、信号处理以及通信工程等专业的本科生和研究生的参考书，也可供广大工程技术人员参考。
Catalogue

第1章MATLAB入门1
1．1MATLAB概述1
1．1．1什么是MATLAB1
1．1．2MATLAB语言特点2
1．1．3MATLAB系统4
1．2MATLAB基本操作5
1．2．1MATLAB用户界面5
1．2．2变量及赋值5
1．2．3绘图命令6
1．2．4MATLAB程序的结构流8
1．3M文件8
1．4本章小结9

第2章时间信号与系统10
2．1离散序列10
2．1．1单位取样序列10
2．1．2单位阶跃序列12
2．1．3矩形序列13
2．1．4正弦序列13
2．1．5实指数序列14
2．1．6复指数序列15
2．1．7周期序列16
2．2信号的产生18
2．2．1方波函数18
2．2．2随机函数19
2．2．3三角波函数19
2．2．4sinc函数20
2．2．5线性调频函数20
2．2．6diric函数21
2．2．7rectpuls函数22
2．2．8tripuls函数23
2．2．9pulstran函数23
2．2．10gauspuls函数24
2．3信号在MATLAB中的运算25
2．3．1信号的时移、反折和尺度变换25
2．3．2信号的加法和乘法运算26
2．3．3信号的奇偶分解29
2．3．4信号的积分和微分30
2．4连续时间系统的时域分析32
2．4．1连续时间系统求解32
2．4．2连续时间系统数值求解32
2．4．3连续时间系统符号求解35
2．4．4连续时间系统卷积求解35
2．5离散时间信号中的运算37
2．5．1离散时间系统响应37
2．5．2离散时间系统的冲激响应和阶跃响应38
2．5．3离散时间信号的卷积和运算39
2．6离散时间系统41
2．6．1离散时间系统的含义41
2．6．2离散时间系统的描述方法42
2．6．3采样定理43
2．7本章小结49

第3章Z变换50
3．1Z变换50
3．1．1Z变换的定义50
3．1．2Z变换的收敛域51
3．2Z反变换52
3．3Z变换的性质54
3．4Z变换在离散系统中的应用57
3．4．1Z域系统函数的零点分析58
3．4．2Z域系统函数的频域分析62
3．4．3Z域系统差分函数求解65
3．5本章小结68

第4章傅里叶变换69
4．1傅里叶变换的形式69
4．2序列的傅里叶变换70
4．2．1周期序列的离散傅里叶级数70
4．2．2非周期序列和周期序列的关系71
4．2．3有限长序列的线性卷积和圆周卷积73
4．2．4有限长序列的傅里叶表示73
4．3离散傅里叶变换75
4．3．1傅里叶级数和傅里叶变换75
4．3．2离散傅里叶级数的性质78
4．3．3离散傅里叶变换的性质79
4．3．4频率抽样80
4．4快速傅里叶变换84
4．4．1按时间抽取的FFT算法84
4．4．2按频率抽取的FFT算法87
4．4．3快速傅里叶变换的MATLAB实现88
4．5Chirp Z变换92
4．6傅里叶变换的应用94
4．6．1离散傅里叶反变换94
4．6．2线性卷积的FFT求法99
4．6．3相关系数的快速求法101
4．7离散余弦变换102
4．8Gabor变换103
4．8．1Gabor变换的定义103
4．8．2Gabor变换的一般求法104
4．8．3Gabor变换的解析理论105
4．9本章小结108

第5章IIR滤波器的设计109
5．1数字滤波器概述109
5．1．1数字滤波器的分类110
5．1．2数字滤波器的设计步骤123
5．2常用模拟低通滤波器的设计124
5．2．1确定系统函数的极点124
5．2．2几种模拟低通滤波器的设计124
5．3根据模拟滤波器设计IIR滤波器142
5．3．1脉冲响应不变法142
5．3．2双线性变换法146
5．4从模拟滤波器低通模型到数字滤波器150
5．4．1低通变换150
5．4．2高通变换151
5．4．3带通变换152
5．4．4带阻变换153
5．5从低通数字滤波器到各种数字滤波器的频率变换154
5．5．1低通-低通155
5．5．2低通-高通155
5．5．3低通-带通158
5．5．4低通-带阻158
5．6本章小结159

第6章FIR滤波器设计160
6．1FIR滤波器的结构160
6．1．1直接型结构161
6．1．2级联型结构161
6．1．3频率抽样型结构161
6．1．4快速卷积型结构166
6．2线性相位FIR滤波器的特性167
6．2．1相位条件167
6．2．2线性相位滤波器的分类168
6．2．3线性相位滤波器的零点特性175
6．3基本窗函数FIR滤波器的设计176
6．3．1窗函数的基本原理176
6．3．2矩形窗179
6．3．3汉宁窗182
6．3．4汉明窗188
6．3．5布莱克曼窗191
6．3．6凯塞窗193
6．3．7窗函数设计法195
6．4频率采样FIR滤波器的设计197
6．4．1设计方法197
6．4．2约束条件198
6．4．3误差设计198
6．5FIR数字滤波器的最优设计204
6．5．1最小均方误差准则205
6．5．2最大误差最小化准则205
6．5．3契比雪夫最佳一致逼近206
6．6FIR与IIR数字滤波器的比较210
6．7本章小结211

第7章其他滤波器212
7．1维纳滤波器212
7．1．1维纳滤波器的基本原理212
7．1．2维纳滤波器的实现218
7．2卡尔曼滤波器222
7．2．1卡尔曼滤波器的基本原理222
7．2．2扩展卡尔曼滤波器和无迹卡尔曼滤波器225
7．3自适应滤波器244
7．3．1自适应滤波器的基本原理244
7．3．2格型自适应滤波器249
7．3．3LS自适应滤波器261
7．4本章小结262

第8章随机信号处理263
8．1随机信号处理概述263
8．1．1随机信号的基本定义263
8．1．2离散随机信号的统计描述264
8．1．3平稳随机序列及其数字特征266
8．1．4平稳随机序列的功率谱267
8．1．5随机序列的各态历经性268
8．1．6特定的随机序列268
8．1．7随机信号处理MATLAB的基本应用268
8．2随机信号的频谱分析271
8．2．1非参量类方法273
8．2．2参量类方法280
8．2．3Subspace Methods子空间法282
8．2．4谱分析的综合应用284
8．3随机信号系统处理模型293
8．3．1AR(1)模型293
8．3．2AR(2)模型294
8．3．3AR(p)模型294
8．3．4MA模型300
8．3．5ARMA模型303
8．4本章小结310

第9章小波分析311
9．1信号的小波变换311
9．1．1信号的连续小波变换312
9．1．2信号的离散小波变换313
9．1．3信号的小波包314
9．1．4常用的小波函数316
9．2信号分析318
9．2．1信号的重构318
9．2．2提升小波在信号中的应用321
9．3信号去噪327
9．3．1小波阈值去噪327
9．3．2小波去噪阈值的选取规则331
9．4小波分析与傅里叶分析的比较332
9．5本章小结334

第10章时频分析工具箱335
10．1时频分析335
10．1．1时频分析的基本理论336
10．1．2短时傅里叶变换336
10．1．3窗函数以及窗函数宽度对时间-频率分辨率的影响339
10．1．4Gabor展开342
10．1．5小波变换345
10．2魏格纳-威利变换347
10．2．1Wigner分布的定义348
10．2．2WVD的性质349
10．2．3WVD的弊端350
10．2．4Wigner分布的实现351
10．2．5Wigner分布中交叉项的的行为353
10．3希尔伯特-黄变换355
10．3．1HHT方法基本定义355
10．3．2EMD分解方法356
10．3．3希尔伯特-黄变换的特点367
10．4时频分析应用368
10．4．1跳频信号的时频分析368
10．4．2调频信号的时频分析370
10．5本章小结379

第11章高阶谱分析380
11．1高阶谱和累量简介380
11．1．1高阶谱380
11．1．2累量的定义381
11．1．3平稳随机过程累量的定义382
11．1．4累量的性质382
11．2高阶谱及其定义383
11．2．1高阶谱定义383
11．2．2高阶谱的性质383
11．2．3高阶谱估计384
11．3高阶谱的简单应用406
11．3．1DOA估计407
11．3．2时延估计411
11．4本章小结415

第12章MATLAB在信号处理中的应用416
12．1瞬时混合盲信号的分离416
12．1．1盲信号分离方法416
12．1．2主成分分析(PCA)421
12．1．3独立分量分析427
12．1．4盲信号处理应用实例432
12．1．5盲信号时频域分离方法438
12．2语音信号分析439
12．2．1语音信号处理方法的基础439
12．2．2语音信号处理方法的应用440
12．3雷达信号处理443
12．3．1雷达信号处理的方法基础443
12．3．2雷达散射截面信号处理448
12．3．3合成孔径雷达信号的处理方法452
12．4本章小结461

参考文献462

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