Neural networks for identification of nonlinear systems under random piecewise polynomial disturbancesTsypkin, Y. Z., Mason , J. D., Avedyan, E. D., Warwick, K. and Levin, I. K. (1999) Neural networks for identification of nonlinear systems under random piecewise polynomial disturbances. IEEE Transactions on Neural Networks, 10 (2). pp. 303-312. ISSN 1045-9227 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1109/72.750559 Abstract/SummaryThe problem of identification of a nonlinear dynamic system is considered. A two-layer neural network is used for the solution of the problem. Systems disturbed with unmeasurable noise are considered, although it is known that the disturbance is a random piecewise polynomial process. Absorption polynomials and nonquadratic loss functions are used to reduce the effect of this disturbance on the estimates of the optimal memory of the neural-network model.
Altmetric Related URLs Deposit Details University Staff: Request a correction | Centaur Editors: Update this record |
Lists
Lists
