Title :
Identification of nonlinear systems with a dynamic recurrent neural network
Author :
Delgado, A. ; Kambhampati, C. ; Warwick, K.
Author_Institution :
Reading Univ., UK
Abstract :
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
Keywords :
identification; nonlinear systems; recurrent neural nets; dynamic recurrent neural network; identification; identified network; nonlinear systems; states;
Conference_Titel :
Artificial Neural Networks, 1995., Fourth International Conference on
Conference_Location :
Cambridge
Print_ISBN :
0-85296-641-5
DOI :
10.1049/cp:19950575
