Identification of nonlinear systems with a dynamic recurrent neural network

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.

Item Type	Conference or Workshop Item (Paper)
URI	https://reading-clone.eprints-hosting.org/id/eprint/21667
Item Type	Conference or Workshop Item
Refereed	Yes
Divisions	Science
Uncontrolled Keywords	dynamic recurrent neural network, identification, identified network, nonlinear systems, states
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