Neural networks for identification of nonlinear systems under random piecewise polynomial disturbances

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From: IEEE Transactions on Neural Networks(Vol. 10, Issue 2)
Publisher: Institute of Electrical and Electronics Engineers, Inc.
Document Type: Article
Length: 79 words

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Abstract :

The 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. Index Terms - Absorption polynomials, disturbance rejection, nonlinear system identification.

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Gale Document Number: GALE|A54335698