2020
DOI: 10.1016/j.neucom.2020.07.036
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Impulsive effects on stability and passivity analysis of memristor-based fractional-order competitive neural networks

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Cited by 152 publications
(42 citation statements)
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“…Corollary 1. Stability: the origin of system (1), with u � 0 and an exact convex representation (35), is exponentially stable if the exist matrices P 1 > 0, P 2j , P 3j , and…”
Section: Theoremmentioning
confidence: 99%
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“…Corollary 1. Stability: the origin of system (1), with u � 0 and an exact convex representation (35), is exponentially stable if the exist matrices P 1 > 0, P 2j , P 3j , and…”
Section: Theoremmentioning
confidence: 99%
“…Stabilization: the origin of system (1) with an exact convex representation (35), under the law of control u � K wω x…”
Section: Theoremmentioning
confidence: 99%
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“…Cheng et al [16] recently proposed an adaptive neural network control approach to achieve accurate and robust control of nonlinear system with uncertain dynamics in which an adaptive neural network is trained online as the controller and combined with PI controller to achieve asymptotically tracking of setpoint. Rajchakit and coworkers [19][20][21] studied the robust dissipativity and stability of different types of neural networks in the face of parametric uncertainties, time-varying delays and stochastic disturbances. The effectiveness of their method is demonstrated through numerical examples.…”
Section: Introductionmentioning
confidence: 99%