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Like no other text in this field, authors Jose C. Principe, Neil R. Euliano, and W. Curt Lefebvre have written a unique and innovative text unifying the concepts of neural networks and adaptive filters into a common framework. The text is suitable for senior/graduate courses in neural networks and adaptive filters. It offers over 200 fully functional simulations (with instructions) to demonstrate and reinforce key concepts and help the reader develop an intuition about the behavior of adaptive systems with real data. This creates a powerful self-learning environment highly suitable for the professional audience.
Jose C. Principe, University of Florida. Neil R. Euliano, NeuroDimension, Inc.W. Curt Lefebvre, NeuroDimension, Inc.
Chapter 1 Data Fitting with Linear Models 1 Chapter 2 Pattern Recognition 68 Chapter 3 Multilayer Perceptrons 100 Chapter 4 Designing and Training MLPS 173 Chapter 5 Function Approximation with MLPs, Radial Basis Functions, and Support Vector Machines 223 Chapter 6 Hebbian Learning and Principal Component Analysis 279 Chapter 7 Competitive and Kohonen Networks 333 Chapter 8 Principles of Digital Signal Processing 364 Chapter 9 Adaptive Filters 429 Chapter 10 Temporal Processing with Neural Networks 473 Chapter 11 Training and Using Recurrent Networks 525Appendix A Elements of Linear Algebra and Pattern Recognition 589Appendix B NeuroSolutions Tutorial 613Appendix C Data Directory 637 Glossary 639 Index 647