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Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models - Rilegato
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Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Contenuti
1. Introduction.- I. Optimization Techniques.- 2. Introduction to Optimization.- 3. Linear Optimization.- 4. Nonlinear Local Optimization.- 5. Nonlinear Global Optimization.- 6. Unsupervised Learning Techniques.- 7. Model Complexity Optimization.- II. Static Models.- 9. Introduction to Static Models.- 10. Linear, Polynomial, and Look-Up Table Models.- 11. Neural Networks.- 12. Fuzzy and Neuro-Fuzzy Models.- 13. Local Linear Neuro-Fuzzy Models: Fundamentals.- 14. Local Linear Neuro-Fuzzy Models: Advanced Aspects.- III. Dynamic Models.- 16. Linear Dynamic System Identification.- 17. Nonlinear Dynamic System Identification.- 18. Classical Polynomial Approaches.- 19. Dynamic Neural and Fuzzy Models.- 20. Dynamic Local Linear Neuro-Fuzzy Models.- 21. Neural Networks with Internal Dynamics.- IV. Applications.- 22. Applications of Static Models.- 23. Applications of Dynamic Models.- 24. Applications of Advanced Methods.- A. Vectors and Matrices.- A.1 Vector and Matrix Derivatives.- A.2 Gradient, Hessian, and Jacobian.- B. Statistics.- B.1 Deterministic and Random Variables.- B.2 Probability Density Function (pdf).- B.3 Stochastic Processes and Ergodicity.- B.4 Expectation.- B.5 Variance.- B.6 Correlation and Covariance.- B.7 Properties of Estimators.- References.
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Nonlinear System Identification : From Classical Approaches to Neural Networks and Fuzzy Models
Editore:
Springer Berlin / Heidelberg, 2000
ISBN 10: 3540673695
ISBN 13: 9783540673699
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Condizione: Very Good. Ships from the UK. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects. Codice articolo 53456331-20
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Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models
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Condizione: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. Codice articolo Z1-U-002-01593
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Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models
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Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models
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Nonlinear System Identification
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Easy and intuitive understandingMany figuresExplanations and terminology from an engineering point-of-viewOnly basic mathematics requiredSelf-contained, no other literature neededWritten from an engineering point of view, this book co. Codice articolo 4898172
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Nonlinear System Identification
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Springer Berlin Heidelberg Nov 2000, 2000
ISBN 10: 3540673695
ISBN 13: 9783540673699
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The goal of this book is to provide engineers and scientIsts in academia and industry with a thorough understanding of the underlying principles of nonlinear system identification. The reader will be able to apply the discussed models and methods to real problems with the necessary confidence and the awareness of potential difficulties that may arise in practice. This book is self-contained in the sense that it requires merely basic knowledge of matrix algebra, signals and systems, and statistics. Therefore, it also serves as an introduction to linear system identification and gives a practical overview on the major optimization methods used in engineering. The emphasis of this book is on an intuitive understanding of the subject and the practical application of the discussed techniques. It is not written in a theorem/proof style; rather the mathematics is kept to a minimum and the pursued ideas are illustrated by numerous figures, examples, and real-world applications. Fifteen years ago, nonlinear system identification was a field of several ad-hoc approaches, each applicable only to a very restricted class of systems. With the advent of neural networks, fuzzy models, and modern structure opti mization techniques a much wider class of systems can be handled. Although one major characteristic of nonlinear systems is that almost every nonlinear system is unique, tools have been developed that allow the use of the same ap proach for a broad variety of systems. 808 pp. Englisch. Codice articolo 9783540673699
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Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models
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Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models
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Nonlinear System Identification
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Condizione: New. pp. 808. Codice articolo 26351810
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