DocumentCode :
447495
Title :
Stabilization of delayed neural networks
Author :
Sanchez, Edgar N. ; Perez, Jose P. ; Perez, Joel
Author_Institution :
CINVESTAV, Jalisco, Mexico
Volume :
3
fYear :
2005
fDate :
10-12 Oct. 2005
Firstpage :
2156
Abstract :
Stability analysis of delayed neural networks has been extensively developed recently. As a continuation of their previous results, in this paper, the authors propose a new methodology for the stabilization of such networks. The approach is based on the inverse optima control technique, which has been introduced to nonlinear system in the last decade of the twentieth century. An example is included to illustrate the applicability of the proposed approach.
Keywords :
delays; neural nets; optimal control; stability; delayed neural networks; inverse optima control technique; stability analysis; Artificial neural networks; Associative memory; Asymptotic stability; Delay effects; Hopfield neural networks; Neural networks; Nonlinear systems; Recurrent neural networks; Stability analysis; Symmetric matrices; Lyapunov; Lyapunov methodology; Recurrent neural networks; delayed nonlinear systems; inverseoptimalcontrol;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2005 IEEE International Conference on
Print_ISBN :
0-7803-9298-1
Type :
conf
DOI :
10.1109/ICSMC.2005.1571468
Filename :
1571468
Link To Document :
بازگشت