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Nonlinear System Identification from classical approaches to neural networks and fuzzy models Oliver Nelles

Por: Tipo de material: TextoTextoDetalles de publicación: New York SpringerDescripción: xvii, 785 p. gráficosISBN:
  • 3540673695
Contenidos:
Introduction
Optimization techniques
Linear optimization
Nonlinear local optimization
Nonlinear global optimization
Unsupervised learning techniques
Model complexity optimization
Introduction to static models
Linear, polynomial and lookup table models
Neural networks
Fuzzy and neurofuzzy models
Local linear neurofuzzy models : fundamentals
Local linear neurofuzzy models . advanced aspects
Linear dynamic system identification
Nonlinear dynamic system identification
Classical polynomial approaches
Dynamic neural and fuzzy models
Dynamic local linear neurofuzzy models
Neural networks with international dynamics
Applications fof static models
Applications of dynamic models
Applications of advanced methods
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Libro Libro Biblioteca Dr. Jorge S. Muntaner Coll 519.7 NEL (Navegar estantería(Abre debajo)) Disponible 006417

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Referencias bibliográficas p. 757778

Introduction

Optimization techniques

Linear optimization

Nonlinear local optimization

Nonlinear global optimization

Unsupervised learning techniques

Model complexity optimization

Introduction to static models

Linear, polynomial and lookup table models

Neural networks

Fuzzy and neurofuzzy models

Local linear neurofuzzy models : fundamentals

Local linear neurofuzzy models . advanced aspects

Linear dynamic system identification

Nonlinear dynamic system identification

Classical polynomial approaches

Dynamic neural and fuzzy models

Dynamic local linear neurofuzzy models

Neural networks with international dynamics

Applications fof static models

Applications of dynamic models

Applications of advanced methods

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