Neural networks for system identification - IEEE Control Systems Magazine

Abstract

This paper presents two approaches for utilization of neural networks in identification of dynamical systems. In the first approach, a Hopfield network is used to implement a least-squares estimation for time-varying and time-invariant systems. The second approach, which is in the frequency domain, utilizes a set of orthogonal basis functions and Fourier… (More)

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Cite this paper

@inproceedings{Chu2004NeuralNF, title={Neural networks for system identification - IEEE Control Systems Magazine}, author={S. Reynold Chu and Rahmat Shoureshi and Manoel Fernando Tenorio}, year={2004} }