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

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

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