Neural Computing Principles (English Version) (English Version)

Author: (USA) Ham
Publisher:
Publish Date: 2003-07-01
Features: This book is an excellent textbook, focusing on the fundamental principles of artificial neural networks and how to apply various neural computing techniques to solve real-world problems in scientific and engineering fields: pattern recognition, optimization, event classification, control and identification of nonlinear systems, and statistical analysis, etc. Algorithms—Most training algorithms are framed with double lines for easy reference to MATLAB functions—Some training algorithms come with accompanying MATLAB function implementations (highlighted in bold in the text). This book is an excellent textbook, focusing on the fundamental principles of artificial neural networks and how to apply various neural computing techniques to solve real-world problems in scientific and engineering fields: pattern recognition, optimization, event classification, control and identification of nonlinear systems, and statistical analysis, etc. Algorithms—Most training algorithms are framed with double lines for easy reference to MATLAB functions—Some training algorithms come with accompanying MATLAB function implementations (highlighted in bold in the text). Code sections are relatively brief and can be input into MATLAB in just a few minutes. MATLAB Toolbox—The book extensively uses MATLAB's Neural Network Toolbox to illustrate certain neural computing concepts. Web Site—Log in to the book's Web site http://www.mhhe.com/engcs/electrical/ham to access new, comprehensive information. Examples—Detailed examples are provided in most chapters to explain important neural computing concepts. Exercise Sets—A large number of exercises applying neural computing techniques are provided at the end of each chapter. Some exercises require the use of MATLAB and MATLAB's Neural Network Toolbox. In some cases, MATLAB function code appendices are also provided. Appendix—Appendix A comprehensively introduces the mathematical foundations of neural computing.