DocumentCode :
1298862
Title :
Absolute stability of global pattern formation and parallel memory storage by competitive neural networks
Author :
Cohen, Michael A. ; Grossberg, Stephen
Author_Institution :
Dept. of Math., Boston Univ., Boston, MA, USA
Issue :
5
fYear :
1983
Firstpage :
815
Lastpage :
826
Abstract :
Systems that are competitive and possess symmetric interactions admit a global Lyapunov function. However, a global Lyapunov function whose equilibrium set can be effectively analyzed has not yet been discovered. It remains an open question whether the Lyapunov function approach, which requires a study of equilibrium points, or an alternative global approach, such as the Lyapunov functional approach, which sidesteps a direct study of equilibrium points will ultimately handle all of the physically important cases.
Keywords :
neural nets; stability; competitive neural networks; equilibrium set; global Lyapunov function; global pattern formation; parallel memory storage; stability; symmetric interactions; Equations; Mathematical model; Neural networks; Pattern formation; Stability analysis; Symmetric matrices; Trajectory;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9472
Type :
jour
DOI :
10.1109/TSMC.1983.6313075
Filename :
6313075
Link To Document :
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