Algorithm.Collections.for.Digital.Signal.Processing.Applications.Using.Matlab

shinechou

Springer 2007年11月新鲜出炉Algorithm.Collections.for.Digital.Signal.Processing.Applications.Using.Matlab，书目录如下：

Chapter 1   ARTIFICIAL INTELLIGENCE  
1 Particle Swarm Algorithm 1
1-1  How are the Values of !(R)x!ˉ and !(R)y!ˉ are Updat
in Every Iteration?  2
1-2 PSO Algorithm to Maximize the Function F(X, Y, Z) 4
1-3 M-program for PSO Algorithm 6
1-4 Program Illustration 8
2 Genetic Algorithm 9
2-1 Roulette Wheel Selection Rule 10
2-2 Example 11
2-2-1 M-program for genetic algorithm 11
2-2-2 Program illustration 13
2-3 Classification of Genetic Operators 15
2-3-1 Simple crossover 16
2-3-2 Heuristic crossover 16
2-3-3 Arith crossover  17
3 Simulated Annealing 18
3-1 Simulated Annealing Algorithm 19
3-2 Example 19
3-3 M-program for Simulated Annealing
4 Back Propagation Neural Network 24
4-1 Single Neuron Architecture 25
4-2 Algorithm 27
4-3 Example 29
4-4 M-program for Training the Artificial Neural Network  
for the Problem Proposed in the Previous Section 31
5 Fuzzy Logic Systems 32
5-1 Union and Intersection of Two Fuzzy Sets 32
5-2 Fuzzy Logic Systems 33
5-2-1 Algorithm 35
5-3 Why Fuzzy Logic Systems? 38
5-4  Example  39
5-5 M-program for the Realization of Fuzzy Logic System  
for the Specifications given in Section 5-4 41
6 Ant Colony Optimization 44
6-1  Algorithm 44
6-2  Example 48
6-3  M-program for Finding the Optimal Order using Ant Colony  
50
Technique for the Specifications given in the Section 6-2
Chapter 2   PROBABILITY AND RANDOM PROCESS
1 Independent Component Analysis 53
1-1 ICA for Two Mixed Signals 53
1-1-1 ICA algorithm  62
1-2 M-file for Independent Component Analysis  65
2 Gaussian Mixture Model 68
2-1 Expectation-maximization Algorithm 70
2-1-1 Expectation stage 71
2-1-2 Maximization stage 71
2-2 Example 72
2-3 Matlab Program 73
2-4 Program Illustration 76
3 K-Means Algorithm for Pattern Recognition 77
3-1 K-means Algorithm  77
3-2 Example 77
3-3 Matlab Program for the K-means Algorithm Applied  
for the Example given in Section 3-2 78
4 Fuzzy K-Means Algorithm for Pattern Recognition  79
4-1 Fuzzy K-means Algorithm  80
4-2 Example 81
4-3 Matlab Program for the Fuzzy k-means Algorithm Applied  
for the Example given in Section 4-2 83
5 Mean and Variance Normalization 84
5-1 Algorithm 84
5-2 Example 1 85
5-3 M-program for Mean and Variance Normalization 86
Chapter 3   NUMERICAL LINEAR ALGEBRA 87
1 Hotelling Transformation 87
1-1 Diagonalization of the Matrix !(R)CM!ˉ 8
1-2 Example 88
1-3 Matlab Program 90
2 Eigen Basis 91
2-1 Example 1   91
3 Singular Value Decomposition (SVD) 93
3-1 Example  94
4 Projection Matrix 95
4-1 Projection of the Vector !(R)a!ˉ on the Vector !(R)b!ˉ
4-2 Projection of the Vector on the Plane Described  
by Two Columns Vectors of the Matrix !(R)X! 96
4-2-1 Example  97
4-2-2 Example 2 98
5 Orthonormal Vectors 100
5-1 Gram-Schmidt Orthogonalization procedure 100
5-2 Example 101
5-3 Need for Orthonormal Basis 101
5-4 M-file for Gram-Schmidt Orthogonalization Procedure 103
6 Computation of the Powers of the Matrix !(R)A!ˉ 10
th
7 Determination of K
  Element in the Sequence 104
8 Computation of Exponential of the Matrix !(R)A!ˉ 10
8.1 Example 107
9 Solving Differential Equation Using Eigen decomposition 108
10 Computation of Pseudo Inverse of the Matrix   109
11 Computation of Transformation Matrices 111
11-1 Computation of Transformation Matrix for the Fourier
113
Transformation   
11-2 Basis Co-efficient transformation 115
11-3 Transformation Matrix for Obtaining Co-efficient  
of Eigen Basis 117
11-4 Transformation Matrix for Obtaining Co-efficient  
of Wavelet Basis 117
12 System Stability Test Using Eigen Values 118
13 Positive Definite Matrix test for Minimal Location  
of the Function f (x1, x2, x3, x4!-xn) 119
14 Wavelet Transformation Using Matrix Method  119
14-1 Haar Transformation  120
14-1-1 Example  122
14-1-2 M-file for haar forward and inverse  
transformation  125
14-2 Daubechies-4 Transformation  127
14-2-1 Example  128
14-2-2 M-file for daubechies 4 forward  
and inverse transformation  131
Chapter 4   SELECTED APPLICATIONS  135
1 Ear Pattern Recognition Using Eigen Ear  135
1-1  Algorithm  135
1-2  M-program for Ear Pattern Recognition  138
1-3  Program    Illustration  140
2 Ear Image Data Compression using Eigen Basis  141
2-1 Approach  141
2-2 M-program for Ear Image Data Compression  143
3 Adaptive Noise Filtering using Back Propagation  
Neural Network  145
3-1  Approach  146
3-2 M-file for Noise Filtering Using ANN  147
3-3  Program Illustration  149
4 Binary Image Rotation Using Transformation Matrix  150
4-1  Algorithm  151
4-2  M-program for Binary Image Rotation with 45 Degree
Anticlockwise Direction  152
5 Clustering Texture Images Using K-means Algorithm  152
5-1  Approach  153
5-2  M-program for Texture Images Clustering  155
6 Search Engine Using Interactive Genetic Algorithm  156
6-1  Procedure  156
6-2  Example  158
6-3  M-program for Interactive Genetic Algorithm  160
6-4  Program Illustration  165
7 Speech Signal Separation and Denoising Using Independent  
Component Analysis  166
7-1  Experiment 1  166
7-2  Experiment 2  167
7-3  M-program for Denoising   169
8 Detecting Photorealistic Images using ICA Basis  170
8-1  Approach  171
8-1-1 To classify the new image into one among the
photographic or photorealistic image  171

8-2  M-program for Detecting Photo Realistic Images  
Using ICA basis  172
8-3  Program Illustration  174
9 Binary Image Watermarking Using Wavelet Domain  
175
of the Audio Signal
9-1  Example  175
9-2 M-file for Binary Image Watermarking  
176
in Wavelet Domain of the Audio Signal
9-3  Program Illustration  180

nov833

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liuwei_0613

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frank12345

感谢楼主的共享

njbbx

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lulinjun_001

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njbbx

好书，拿来就可以用了，一定要支持

harold

seems good

smaa

真是好人
thx