DocumentCode
2648682
Title
Absolute stability of asymmetric Hopfield neural network
Author
Gao, Weibing ; Xiong, Yi
Author_Institution
Seventh Res. Div., Beijing Univ. of Aeronaut. & Astronaut., China
fYear
1991
fDate
18-21 Nov 1991
Firstpage
2195
Abstract
A sufficient absolute stability condition of the asymmetric Hopfield network in terms of the weight matrix is presented. The approach is to reformulate the neural network equation into a nonlinear multivariable feedback system. The authors apply results from nonlinear control system stability theory to derive a sufficient condition to ensure that an asymmetric Hopfield type network equilibrium point is absolutely stable
Keywords
neural nets; nonlinear control systems; stability; absolute stability; asymmetric Hopfield neural network; network equilibrium point; nonlinear multivariable feedback system; sufficient condition; weight matrix; Biological neural networks; Brain modeling; Capacitance; Hopfield neural networks; Large-scale systems; Neural networks; Neurofeedback; Nonlinear control systems; Nonlinear systems; Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN
0-7803-0227-3
Type
conf
DOI
10.1109/IJCNN.1991.170713
Filename
170713
Link To Document