Title :
Relative degree of recurrent neural networks
Author :
Delgado, A. ; Kambhampati, C.
Author_Institution :
Reading Univ., UK
Abstract :
In the paper some tools from the differential geometry theory of single-input single-output nonlinear systems are applied to a recurrent neural network. It is shown that a change of coordinates and a state feedback can transform a recurrent neural network in to a linear system
Keywords :
differential geometry; feedback; nonlinear systems; recurrent neural nets; differential geometry; linear system; recurrent neural networks; relative degree; single-input single-output nonlinear systems; state feedback;
Conference_Titel :
Intelligent Systems Engineering, 1994., Second International Conference on
Conference_Location :
Hamburg-Harburg
Print_ISBN :
0-85296-621-0
DOI :
10.1049/cp:19940611
