Algorithm Collections for Digital Signal Processing Applications Using Matlab [Hardcover]

The Algorithms such as SVD, Eigen decomposition, Gaussian Mixture Model, HMM etc. are presently scattered in different fields. There remains a need to collect all such algorithms for quick reference. Also there is the need to view such algorithms in application point of view. This book attempts to satisfy the above requirement. The algorithms are made clear using MATLAB programs.

The Algorithms such as SVD, Eigen decomposition, Gaussian Mixture Model, HMM etc. are scattered in different fields. There is the need to collect all such algorithms for quick reference. Also there is the need to view such algorithms in application point of view. Algorithm Collections for Digital Signal Processing Applications using MATLAB attempts to satisfy the above requirement. Also the algorithms are made clear using MATLAB programs.

Preface. Acknowledgments.Chapter 1 ARTIFICIAL INTELLIGENCE.1 Particle Swarm Algorithm. 1-1 How are the values for the variables 'x' and 'y' are updated in every Iteration? 1-2 PSO Algorithm to maximize the function F(X,Y,Z). 1-3 m-Program for PSO Algorithm. 1-4 Program Illustration.2 Genetic Algorithm. 2-1 Roulette Wheel Selection Rule. 2-2 Example. 2-2-1 m-Program for Genetic Algorithm. 2-2-2 Program Illustration. 2-3 Classification of Genetic Operators. 2-3-1 Simple Crossover. 2-3-2 Heuristic Crossover. 2-3-3 Arith crossover.3 Simulated Annealing. 3-1 Simulated Annealing algorithm. 3-2 Example. 3-3 m-program for simulated Annealing.4 Back propagation Neural Network. 4-1 Single Neuron architecture. 4-2 Algorithm. 4-3 Example. 4-4 m-program for training the Artificial Neural Network for the problem proposed in the previous section.5 Fuzzy Logic Systems. 5-1 Union and Intersection of two fuzzy sets. 5-2 Fuzzy logic systems. 5-2-1 Algorithm. 5-3 Why Fuzzy logic systems? 5-4 Example. 5-5 m-program for the realization of fuzzy logic system for the Specifications given in section 5-4.6 Ant Colony OptimizalăŔ