Nonlinear System Identification

Oliver Nelles

Note moyenne 
Oliver Nelles - Nonlinear System Identification.
The book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. Additionally, it provides the... Lire la suite
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Résumé

The book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. Additionally, it provides the reader with the necessary background on optimization techniques making the book self-contained. The emphasis is put on modem methods based on neural networks and fuzzy systems without neglecting the classical approaches. The entire book is written from an engineering point-of-view, focusing on the intuitive understanding of the basic relationships. This is supported by many illustrative figures. Advanced mathematics is avoided. Thus, the book is suitable for last year undergraduate and graduate courses as well as research and development engineers in industries.

Sommaire

  • OPTIMIZATION TECHNIQUES
    • Introduction to Optimization
    • Linear Optimization
    • Nonlinear Local Optimization
    • Nonlinear Global Optimization
    • Unsupervised Learning Techniques
    • Model Complexity Optimization
  • STATIC MODELS
    • Introduction
    • Linear, Polynomial, and Look-Up Table Models
    • Neural Networks
    • Fuzzy and Neuro-Fuzzy Models
    • Local Linear Neuro-Fuzzy Models : Fundamentals
    • Local Linear Neuro-Fuzzy Models : Advanced Aspects
  • DYNAMIC MODELS
    • Linear Dynamic System Identification
    • Nonlinear Dynamic System Identification
    • Classical Polynomial Approaches
    • Dynamic Neural and Fuzzy Models
    • Dynamic Local Linear Neuro-Fuzzy Models
  • APPLICATIONS
    • Applications of Static Models
    • Applications of Dynamic Models
    • Applications of Advanced Methods.

Caractéristiques

  • Date de parution
    01/01/2001
  • Editeur
  • ISBN
    3-540-67369-5
  • EAN
    9783540673699
  • Présentation
    Relié
  • Nb. de pages
    785 pages
  • Poids
    1.245 Kg
  • Dimensions
    16,0 cm × 24,0 cm × 3,5 cm

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