Title :
Input-to-state stability (ISS) analysis for dynamic neural networks
Author :
Sanchez, Edgar N. ; Perez, Jose P.
Author_Institution :
Univ. Guadalajara, Jalisco, Mexico
Abstract :
This paper presents the input-to-state (ISS) analysis for dynamic neural networks. We determine, using a Lyapunov function, conditions to guarantee ISS; they also guarantee globally asymptotically stability
Keywords :
asymptotic stability; matrix algebra; neural nets; Lyapunov function; dynamic neural networks; globally asymptotically stability; input-to-state stability analysis; Associative memory; Asymptotic stability; Electronic mail; Intelligent control; Lyapunov method; Mathematical model; Neural networks; Nonlinear systems; Pattern recognition; Stability analysis;
Conference_Titel :
Neural Networks,1997., International Conference on
Conference_Location :
Houston, TX
Print_ISBN :
0-7803-4122-8
DOI :
10.1109/ICNN.1997.616191
