Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/7758
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tojtovska, Biljana | en_US |
dc.contributor.author | Jankovic, Svetlana | en_US |
dc.date.accessioned | 2020-04-26T06:13:02Z | - |
dc.date.available | 2020-04-26T06:13:02Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | B. Tojtovska, S. Jankovic, On a general decay stability of stochastic Cohen–Grossberg neural networks with time-varying delays, Applied Mathematics and Computation (Elsevier) 219 (2012), pp. 2289-2302 | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/7758 | - |
dc.description.abstract | To the best of our knowledge, there are only few results on general decay stability applied to stochastic neural networks. For stochastic Cohen–Grossberg neural networks with time-varying delays, we study in the present paper both the pth moment and almost sure stability on a general decay rate and partly generalize and improve some known results referring to the exponential stability. We also extend the usual notion on a general decay function, which allows us to study both the pth moment and almost sure stability even if the exponential stability cannot be shown. Some examples are presented to support and illustrate the theory. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.relation | Supported by Grant No. 174007 of MNTRS | en_US |
dc.relation.ispartof | Applied Mathematics and Computation | en_US |
dc.subject | Stochastic neural networks, Time-varying delays, Moment stability, Almost sure stability, Decay function | en_US |
dc.title | On a general decay stability of stochastic Cohen–Grossberg neural networks with time-varying delays | en_US |
dc.type | Journal Article | en_US |
dc.identifier.doi | https://doi.org/10.1016/j.amc.2012.08.076 | - |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
Appears in Collections: | Faculty of Computer Science and Engineering: Journal Articles |
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