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More copies of this ISBN:Other titles in the MATLAB Curriculum Series series:Neuro-fuzzy Modeling and Soft Computing (97 Edition)by Jyh-shing Roger Jang
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Synopses & ReviewsPublisher Comments: Neuro-Fuzzy Modeling and Soft Computing places particular emphasis on the theoretical aspects of covered methodologies, as well as empirical observations and verifications of various applications in practice. Neuro-Fuzzy Modeling and Soft Computing is oriented toward methodologies that are likely to be of practical use. It includes exercises, some of which involve MATLAB programming tasks to provide readers with hands-on programming experiences for practical problem-solving. Each chapter also includes a reference list to the research literature so that readers may pursue topics in greater depth. This book is suitable as a self-study guide by researchers who want to learn basic and advanced neuro-fuzzy and soft computing within the framework of computational intelligence. Book News Annotation:Unlike traditional, hard computing, this field aims to accommodate
the pervasive imprecision of the real world, using the human mind as
its role model. Intended for use as a graduate level text, or a
self- study guide for students and researchers, this book presents an
introduction to the field, and then covers fuzzy set theory,
regression and optimization, neutral networks, neuro-fuzzy modeling
and controls, and advanced applications. It also includes hints to
selected exercises, and lists of Internet resources, MATLAB programs,
and acronyms. Contains an offer for free companion software.
Annotation c. Book News, Inc., Portland, OR (booknews.com) Synopsis:"Neuro-Fuzzy Modeling and Soft Computing" places particular emphasis on the theoretical aspects of covered methodologies, as well as empirical observations and verifications of various applications in practice. "Neuro-Fuzzy Modeling and Soft Computing" is oriented toward methodologies that are likely to be of practical use. It includes exercises, some of which involve MATLAB programming tasks to provide readers with hands-on programming experiences for practical problem-solving. Each chapter also includes a reference list to the research literature so that readers may pursue topics in greater depth. This book is suitable as a self-study guide by researchers who want to learn basic and advanced neuro-fuzzy and soft computing within the framework of computational intelligence.
Table of Contents1. Introduction to Neuro-Fuzzy and Soft Computing.
I. FUZZY SET THEORY. 2. Fuzzy Sets.
3. Fuzzy Rules and Fuzzy Reasoning.
4. Fuzzy Inference Systems.
II. REGRESSION AND OPTIMIZATION. 5. Least-Squares Methods for System Identification.
6. Derivative-Based Optimization.
7. Derivative-Free Optimization.
III. NEURAL NETWORKS. 8. Adaptive Networks.
9. Supervised Learning Neural Networks.
10. Learning from Reinforcement.
11. Unsupervised Learning and Other Neural Networks.
IV. NEURO-FUZZY MODELING. 12. ANFIS: Adaptive-Networks-based Fuzzy Inference Systems.
13. Coactive Neuro-Fuzzy Modeling: Towards Generalized ANFIS.
V. ADVANCED NEURO-FUZZY MODELING. 14. Classification and Regression Trees.
15. Data Clustering Algorithms.
16. Rulebase Structure Identification.
VI. NEURO-FUZZY CONTROL. 17. Neuro-Fuzzy Control I.
18. Neuro-Fuzzy Control II.
VII. ADVANCED APPLICATIONS. 19. ANFIS Applications.
20. Fuzzy-Filtered Neural Networks.
21. Fuzzy Theory and Genetic Algorithms in Game Playing.
22. Soft Computing for Color Recipe Prediction. What Our Readers Are SayingBe the first to add a comment for a chance to win!Product Details
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