Stock image for illustration purposes only - book cover, edition or condition may vary.
Discrete-time High Order Neural Control
Sanchez, Edgar N.; Alanis, Alma Y.; Loukianov, Alexander G.
€ 120.78
FREE Delivery in Ireland
Description for Discrete-time High Order Neural Control
Hardback. Intends to present the advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple outputs. This book presents solutions for the output trajectory tracking problem of unknown nonlinear systems based on four schemes. Series: Studies in Computational Intelligence. Num Pages: 120 pages, 4 black & white tables, biography. BIC Classification: TJF. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 7. Weight in Grams: 770.
Neural networks have become a well-established methodology as exempli?ed by their applications to identi?cation and control of general nonlinear and complex systems; the use of high order neural networks for modeling and learning has recently increased. Usingneuralnetworks,controlalgorithmscanbedevelopedtoberobustto uncertainties and modeling errors. The most used NN structures are Feedf- ward networks and Recurrent networks. The latter type o?ers a better suited tool to model and control of nonlinear systems. There exist di?erent training algorithms for neural networks, which, h- ever, normally encounter some technical problems such as local minima, slow learning, and high sensitivity to initial conditions, among others. As a ... Read more
Neural networks have become a well-established methodology as exempli?ed by their applications to identi?cation and control of general nonlinear and complex systems; the use of high order neural networks for modeling and learning has recently increased. Usingneuralnetworks,controlalgorithmscanbedevelopedtoberobustto uncertainties and modeling errors. The most used NN structures are Feedf- ward networks and Recurrent networks. The latter type o?ers a better suited tool to model and control of nonlinear systems. There exist di?erent training algorithms for neural networks, which, h- ever, normally encounter some technical problems such as local minima, slow learning, and high sensitivity to initial conditions, among others. As a ... Read more
Product Details
Format
Hardback
Publication date
2008
Publisher
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Germany
Number of pages
120
Condition
New
Series
Studies in Computational Intelligence
Number of Pages
110
Place of Publication
Berlin, Germany
ISBN
9783540782889
SKU
V9783540782889
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Discrete-time High Order Neural Control