Page 7 - Algorithm Collections for Digital Signal Processing Applications using MATLAB

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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