This concise but comprehensive textbook reviews the most popular neural-network methods and their associated techniques. Each chapter provides state-of-the-art descriptions of important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms a powerful tools for neural-network learning a are introduced. The systematic survey of neural-network models and exhaustive references list will point readers toward topics for future research. The algorithms outlined also make this textbook a valuable reference for scientists and practitioners working in pattern recognition, signal processing, speech and image processing, data analysis and artificial intelligence.For example, for the complex PCA, one can minimize the MSE function E = 1 N N a i=1 ay ayzi a WWHzi ay ay2 (7.141) ... 5 The MATLAB code for the NLCPCA can be downloaded from http://www.ocgy.ubc.ca/projects/clim.pred/download. html.
|Title||:||Neural Networks in a Softcomputing Framework|
|Author||:||Ke-Lin Du, M.N.S. Swamy|
|Publisher||:||Springer Science & Business Media - 2006-08-02|