Nonlinear System Identification : From Classical Approaches to Neural Networks and Fuzzy Models /
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 modern methods based on neural...
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| Format: | eBook |
| Language: | English |
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Berlin, Heidelberg :
Springer Berlin Heidelberg,
2001.
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| Online Access: | Connect to the full text of this electronic book |
| Summary: | 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 modern 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. The new edition includes exercises. |
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| Item Description: | Electronic resource. |
| Physical Description: | 1 online resource (xvii, 785 pages) |
| ISBN: | 9783662043233 (electronic bk.) 3662043238 (electronic bk.) |