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Cited by 11 publications
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References 27 publications
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“…In many cases, stability with respect to a general decay function is also of interest. Only few results in the literature consider this general decay in the case of neural networks-in [23][24][25] the authors analyze models of stochastic neural networks with and without time delay and impulses. However, to best of our knowledge, there are no results on stability analysis on a system of coupled stochastic Cohen-Grossberg neural networks, which include time delays, impulses and Markovian switching.…”
Section: Introductionmentioning
confidence: 99%
“…In many cases, stability with respect to a general decay function is also of interest. Only few results in the literature consider this general decay in the case of neural networks-in [23][24][25] the authors analyze models of stochastic neural networks with and without time delay and impulses. However, to best of our knowledge, there are no results on stability analysis on a system of coupled stochastic Cohen-Grossberg neural networks, which include time delays, impulses and Markovian switching.…”
Section: Introductionmentioning
confidence: 99%
“…So, the stochastic disturbance is probably the main resource of the performance degradation in the implemented neural networks. Therefore, the stability of stochastic neural networks with delay has attracted increasing interests and some results related to stochastic disturbances have been published . Recently, a class of neural networks with Markovian jump parameters has received a great deal of research attention because this class of neural networks has been recognized to be the best system to model the phenomenon of information latching and the abrupt phenomena such as random failures or repairs of the components, sudden environmental changes, changing subsystem interconnections, and so forth.…”
Section: Introductionmentioning
confidence: 99%
“…With respect to stochastic neural networks, there are many works on the stability. For example, in [11][12][13][14][15][16][17], the scholars studied the stability of different classes of stochastic neural networks. For other results on stochastic neural networks, the reader may see [18][19][20][21][22][23] and the references therein.…”
Section: Introductionmentioning
confidence: 99%