Referenced Items are not available for this document.
The componentwise stability is a special type of asymptotic stability which ensures the individual monitoring of each state-space variable of a dynamical system. For an interval Hopfield neural network (IHNN), sufficient conditions are provided to analyze the absolute componentwise stability with respect to a class of activation functions (CAF). Both continuous- and discrete-time dynamics are considered. The conditions are formulated in terms of Hurwitz/Schur stability of a test matrix built from the information about the CAF and the interval matrices defining the IHNN. Some interesting results are derived as particular cases, which allow comparisons with several other works.
Published in:
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
(Volume:35
,
Issue:
1
)
Date of Publication: Feb. 2005
- Page(s):
- 136 - 141
- ISSN :
- 1083-4419
- INSPEC Accession Number:
- 8257521
- Digital Object Identifier :
- 10.1109/TSMCB.2004.839246
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 24 January 2005
- Issue Date :
- Feb. 2005
- Sponsored by :
- IEEE Systems, Man, and Cybernetics Society
- PubMed ID :
- 15719942
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