Identification of nonlinear systems with a dynamic recurrent neural network

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Delgado, A., Kambhampati, C. and Warwick, K. (1995) Identification of nonlinear systems with a dynamic recurrent neural network. In: Fourth International Conference on Artificial Neural Networks, 26-28 June 1995, Cambridge, UK, pp. 318-322. doi: 10.1049/cp:19950575

Abstract/Summary

Two approaches are presented to calculate the weights for a Dynamic Recurrent Neural Network (DRNN) in order to identify the input-output dynamics of a class of nonlinear systems. The number of states of the identified network is constrained to be the same as the number of states of the plant.

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Item Type	Conference or Workshop Item (Paper)
URI	https://reading-clone.eprints-hosting.org/id/eprint/21667
Identification Number/DOI	10.1049/cp:19950575
Refereed	Yes
Divisions	Science
Uncontrolled Keywords	dynamic recurrent neural network, identification, identified network, nonlinear systems, states
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Date Deposited:	27 Jul 2011 15:02	Date item deposited into CentAUR
Last Modified:	09 Jul 2021 08:26	Date item last modified

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