Referenced Items are not available for this document.
This brief paper presents an M-matrix-based algebraic criterion for the global exponential stability of a class of recurrent neural networks with decreasing time-varying delays. The criterion improves some previous criteria based on M-matrix and is easy to be verified with the connection weights of the recurrent neural networks with decreasing time-varying delays. In addition, the rate of exponential convergence can be estimated via a simple computation based on the criterion herein.
Published in:
Neural Networks, IEEE Transactions on
(Volume:19
,
Issue:
3
)
Date of Publication: March 2008
- Page(s):
- 528 - 531
- ISSN :
- 1045-9227
- INSPEC Accession Number:
- 9913766
- Digital Object Identifier :
- 10.1109/TNN.2007.911751
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 26 February 2008
- Issue Date :
- March 2008
- Sponsored by :
- IEEE Computational Intelligence Society
- PubMed ID :
- 18334371
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