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Nonlinear System Identification

Overview of attention for book
Nonlinear System Identification
Springer Berlin Heidelberg

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Introduction to Optimization
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    Chapter 3 Linear Optimization
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    Chapter 4 Nonlinear Local Optimization
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    Chapter 5 Nonlinear Global Optimization
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    Chapter 6 Unsupervised Learning Techniques
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    Chapter 7 Model Complexity Optimization
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    Chapter 8 Introduction to Static Models
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    Chapter 9 Linear, Polynomial, and Look-Up Table Models
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    Chapter 10 Neural Networks
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    Chapter 11 Fuzzy and Neuro-Fuzzy Models
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    Chapter 12 Local Linear Neuro-Fuzzy Models: Fundamentals
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    Chapter 13 Local Linear Neuro-Fuzzy Models: Advanced Aspects
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    Chapter 14 Linear Dynamic System Identification
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    Chapter 15 Nonlinear Dynamic System Identification
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    Chapter 16 Classical Polynomial Approaches
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    Chapter 17 Dynamic Neural and Fuzzy Models
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    Chapter 18 Dynamic Local Linear Neuro-Fuzzy Models
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    Chapter 19 Neural Networks with Internal Dynamics
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    Chapter 20 Applications of Static Models
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    Chapter 21 Applications of Dynamic Models
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    Chapter 22 Applications of Advanced Methods
Attention for Chapter 7: Model Complexity Optimization
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