DocumentCode
771347
Title
High-order absolutely stable neural networks
Author
Dembo, Amir ; Farotimi, Oluseyi ; Kailath, Thomas
Author_Institution
Dept. of Electr. Eng., Stanford Univ., CA, USA
Volume
38
Issue
1
fYear
1991
fDate
1/1/1991 12:00:00 AM
Firstpage
57
Lastpage
65
Abstract
The stability properties of arbitrary order continuous-time dynamic neural networks are studied in the spirit of an earlier analysis of a first-order system by M.A. Cohen and S. Grossberg (1983). The corresponding class of Lyapunov function is presented and the equilibrium points are characterized. The relationships with other continuous-time models are pointed out
Keywords
Lyapunov methods; convergence; neural nets; polynomials; stability; Lyapunov function; arbitrary order; continuous-time; dynamic networks; equilibrium points; high order type; neural networks; stability properties; Associative memory; Circuit stability; Circuits and systems; Linear programming; Lyapunov method; Neural networks; Neurons; Pattern recognition; Stability analysis; State estimation;
fLanguage
English
Journal_Title
Circuits and Systems, IEEE Transactions on
Publisher
ieee
ISSN
0098-4094
Type
jour
DOI
10.1109/31.101303
Filename
101303
Link To Document