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130626 ||| eng |
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|a 9783540315964
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| 100 |
1 |
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|a Janczak, Andrzej
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| 245 |
0 |
0 |
|a Identification of Nonlinear Systems Using Neural Networks and Polynomial Models
|h Elektronische Ressource
|b A Block-Oriented Approach
|c by Andrzej Janczak
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| 250 |
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|a 1st ed. 2005
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| 260 |
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|a Berlin, Heidelberg
|b Springer Berlin Heidelberg
|c 2005, 2005
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| 300 |
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|a XIV, 199 p
|b online resource
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| 505 |
0 |
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|a Introduction -- Neural network Wiener models -- Neural network Hammerstein models -- Polynomial Wiener models -- Polynomial Hammerstein models -- Applications
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| 653 |
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|a Mechanics, Applied
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| 653 |
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|a Complex Systems
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| 653 |
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|a Control, Robotics, Automation
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| 653 |
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|a Control theory
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| 653 |
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|a Systems Theory, Control
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| 653 |
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|a Multibody Systems and Mechanical Vibrations
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| 653 |
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|a System theory
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| 653 |
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|a Vibration
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| 653 |
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|a Control engineering
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| 653 |
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|a Robotics
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| 653 |
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|a Mathematical physics
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| 653 |
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|a Multibody systems
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| 653 |
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|a Automation
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| 653 |
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|a Theoretical, Mathematical and Computational Physics
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Lecture Notes in Control and Information Sciences
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| 028 |
5 |
0 |
|a 10.1007/b98334
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/b98334?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 629.8
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| 520 |
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|a This monograph systematically presents the existing identification methods of nonlinear systems using the block-oriented approach It surveys various known approaches to the identification of Wiener and Hammerstein systems which are applicable to both neural network and polynomial models. The book gives a comparative study of their gradient approximation accuracy, computational complexity, and convergence rates and furthermore presents some new and original methods concerning the model parameter adjusting with gradient-based techniques. "Identification of Nonlinear Systems Using Neural Networks and Polynomal Models" is useful for researchers, engineers and graduate students in nonlinear systems and neural network theory
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