DocumentCode
1277893
Title
Estimate of exponential convergence rate and exponential stability for neural networks
Author
Yi, Zhang ; Heng, P.A. ; Fu, Ada W C
Author_Institution
Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
Volume
10
Issue
6
fYear
1999
fDate
11/1/1999 12:00:00 AM
Firstpage
1487
Lastpage
1493
Abstract
Estimates of exponential convergence rate and exponential stability are studied for a class of neural networks which includes Hopfield neural networks and cellular neural networks. Both local and global exponential convergence are discussed. Theorems for estimation of the exponential convergence rate are established and the bounds on the rate of convergence are given. The domains of attraction in the case of local exponential convergence are obtained. Simple conditions are presented for checking exponential stability of the neural networks
Keywords
asymptotic stability; convergence; matrix algebra; neural nets; Hopfield neural networks; cellular neural networks; domains of attraction; exponential convergence rate; exponential stability; global convergence; local convergence; Asymptotic stability; Cellular neural networks; Computer networks; Convergence; Differential equations; Estimation theory; Hopfield neural networks; Neural networks; Neurons; Stability analysis;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.809094
Filename
809094
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