Use of multilayer feedforward neural networks in identification and control of Wiener model
dc.contributor.author | Chandrasekar, V., author | |
dc.contributor.author | Karim, M. N., author | |
dc.contributor.author | Al-Duwaish, H., author | |
dc.contributor.author | IEE, publisher | |
dc.date.accessioned | 2007-01-03T08:10:59Z | |
dc.date.available | 2007-01-03T08:10:59Z | |
dc.date.issued | 1996 | |
dc.description.abstract | The problem of identification and control of a Wiener model is studied. The proposed identification model uses a hybrid model consisting of a linear autoregressive moving average model in cascade with a multilayer feed forward neural network. A two-step procedure is proposed to estimate the linear and nonlinear parts separately. Control of the Wiener model can be achieved by inserting the inverse of the static nonlinearity in the appropriate loop locations. Simulation results illustrate the performance of the proposed method. | |
dc.format.medium | born digital | |
dc.format.medium | proceedings (reports) | |
dc.identifier.bibliographicCitation | Al-Duwaish, H., M. N. Karim, and V. Chandrasekar, Use of Multilayer Feedforward Neural Networks in Identification and Control of Wiener Model, IEE Proceedings. Control Theory and Applications 143, no. 3 (May 1996): 255-258. | |
dc.identifier.uri | http://hdl.handle.net/10217/68053 | |
dc.language | English | |
dc.language.iso | eng | |
dc.publisher | Colorado State University. Libraries | |
dc.relation.ispartof | Faculty Publications | |
dc.rights | ©1996 IEE. | |
dc.rights | Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. | |
dc.subject | nonlinear system identification | |
dc.subject | Wiener model | |
dc.subject | neural networks | |
dc.title | Use of multilayer feedforward neural networks in identification and control of Wiener model | |
dc.type | Text |
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