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Download fileOn stability of recurrent neural networks : an approach from volterra integro-differential equations
The uniform asymptotic stability of recurrent neural networks (RNNs) with distributed delay is analyzed by comparing RNNs to linear Volterra integro-differential systems under Lipschitz continuity of activation functions. The stability criteria obtained have unified and extended many existing results on RNNs.
Funding
Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)
History
Volume
17Issue
1Start Page
264End Page
267Number of Pages
4eISSN
1941-0093ISSN
1045-9227Location
New York (NY)Publisher
Institute of Electrical and Electronics EngineersPublisher DOI
Full Text URL
Language
en-ausPeer Reviewed
- Yes
Open Access
- No
External Author Affiliations
Faculty of Business and Informatics; Flinders University; TBA Research Institute;Era Eligible
- Yes