Neural and Adaptive Systems
-15%
portes grátis
Neural and Adaptive Systems
Fundamentals through Simulations
Principe, Jose C.; Euliano, Neil R.; Lefebvre, W. Curt
John Wiley & Sons Inc
01/2000
672
Mole
Inglês
9780471351672
15 a 20 dias
1234
Descrição não disponível.
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 525
Appendix A Elements of Linear Algebra and Pattern Recognition 589
Appendix B NeuroSolutions Tutorial 613
Appendix C Data Directory 637
Glossary 639
Index 647
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 525
Appendix A Elements of Linear Algebra and Pattern Recognition 589
Appendix B NeuroSolutions Tutorial 613
Appendix C Data Directory 637
Glossary 639
Index 647
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insight; develop; adaptive; oneofakind; book; new; interactive; behavior; engineering; project; systems; part; science; concepts; filters; framework; neural; common; fundamentals; classification; pattern; linear regression
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 525
Appendix A Elements of Linear Algebra and Pattern Recognition 589
Appendix B NeuroSolutions Tutorial 613
Appendix C Data Directory 637
Glossary 639
Index 647
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 525
Appendix A Elements of Linear Algebra and Pattern Recognition 589
Appendix B NeuroSolutions Tutorial 613
Appendix C Data Directory 637
Glossary 639
Index 647
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
