| Identification and control of dynamical systems using neural networks. | |
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MedLine Citation:
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PMID: 18282820 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems. The emphasis is on models for both identification and control. Static and dynamic backpropagation methods for the adjustment of parameters are discussed. In the models that are introduced, multilayer and recurrent networks are interconnected in novel configurations, and hence there is a real need to study them in a unified fashion. Simulation results reveal that the identification and adaptive control schemes suggested are practically feasible. Basic concepts and definitions are introduced throughout, and theoretical questions that have to be addressed are also described. |
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Authors:
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K S Narendra; K Parthasarathy |
Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council Volume: 1 ISSN: 1045-9227 ISO Abbreviation: IEEE Trans Neural Netw Publication Date: 1990 |
Date Detail:
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Created Date: 2008-02-19 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101211035 Medline TA: IEEE Trans Neural Netw Country: United States |
Other Details:
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Languages: eng Pagination: 4-27 Citation Subset: - |
Affiliation:
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Dept. of Electr. Eng., Yale Univ., New Haven, CT. |
Export Citation:
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Descriptor/Qualifier:
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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