2013
DOI: 10.1016/j.neucom.2013.01.028
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Adaptive synchronization for stochastic T–S fuzzy neural networks with time-delay and Markovian jumping parameters

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Cited by 62 publications
(20 citation statements)
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“…And the dynamic behavior of neural networks contains inherent time delays, which may cause instability or oscillation. This kind of neural networks are widely studied by many scholars [1][2][3][4][5][6][7][8].…”
Section: Introductionmentioning
confidence: 99%
“…And the dynamic behavior of neural networks contains inherent time delays, which may cause instability or oscillation. This kind of neural networks are widely studied by many scholars [1][2][3][4][5][6][7][8].…”
Section: Introductionmentioning
confidence: 99%
“…In this case, there exist finite modes which may be switched from one to another at different times in the neural networks. This kind of systems are widely studied by many researchers [11][12][13][14][15][16][17][18][19].…”
Section: Introductionmentioning
confidence: 99%
“…Recently, Markovian jump systems have received many increasing research interests [7][8][9]. The reason that Markovian jump systems have been paid a great deal of attention is that they are often employed to model the abrupt phenomena such as random failures of the components and sudden environmental changes.…”
Section: Introductionmentioning
confidence: 99%