DocumentCode
315255
Title
Input-to-state stability (ISS) analysis for dynamic neural networks
Author
Sanchez, Edgar N. ; Perez, Jose P.
Author_Institution
Univ. Guadalajara, Jalisco, Mexico
Volume
2
fYear
1997
fDate
9-12 Jun 1997
Firstpage
1139
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks,1997., International Conference on
Conference_Location
Houston, TX
Print_ISBN
0-7803-4122-8
Type
conf
DOI
10.1109/ICNN.1997.616191
Filename
616191
Link To Document