DocumentCode
1428546
Title
Stability of asymmetric Hopfield networks
Author
Chen, Tianping ; Amari, Shun Ichi
Author_Institution
Inst. of Math., Fudan Univ., Shanghai, China
Volume
12
Issue
1
fYear
2001
fDate
1/1/2001 12:00:00 AM
Firstpage
159
Lastpage
163
Abstract
In this paper, we discuss dynamical behaviors of recurrently asymmetrically connected neural networks in detail. We propose an effective approach to study global and local stability of the networks. Many of well known existing results are unified in our framework, which gives much better test conditions for global and local stability. Sufficient conditions for the uniqueness of the equilibrium point and its stability conditions are given, too
Keywords
Hopfield neural nets; recurrent neural nets; stability criteria; asymmetric Hopfield networks; dynamical behaviors; equilibrium point; global stability; local stability; recurrently asymmetrically connected neural networks; stability conditions; stability criteria; Chaos; Differential equations; Hopfield neural networks; Lyapunov method; Mathematics; Neural networks; Recurrent neural networks; Stability; Sufficient conditions; Testing;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.896806
Filename
896806
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