DocumentCode
1277790
Title
Asymptotic behavior of irreducible excitatory networks of analog graded-response neurons
Author
Pakdaman, K. ; Malta, C.P. ; Grotta-Ragazzo, C.
Author_Institution
Dept. of Biophys. Eng., Osaka Univ., Japan
Volume
10
Issue
6
fYear
1999
fDate
11/1/1999 12:00:00 AM
Firstpage
1375
Lastpage
1381
Abstract
In irreducible excitatory networks of analog graded-response neurons, the trajectories of most solutions tend to the equilibria. We derive sufficient conditions for such networks to be globally asymptotically stable. When the network possesses several locally stable equilibria, their location in the phase space is discussed and a description of their attraction basin is given. The results hold even when interunit transmission is delayed
Keywords
Lyapunov methods; asymptotic stability; feedback; recurrent neural nets; analog graded-response neurons; asymptotic behavior; attraction basin; global asymptotic stability; interunit transmission; irreducible excitatory networks; locally stable equilibria; phase space; sufficient conditions; Convergence; Delay; Differential equations; Displays; Feedback loop; Joining processes; Neural networks; Neurons; Stationary state; Sufficient conditions;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.809082
Filename
809082
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