Finite-time synchronization of coupled time-delayed neural networks with discontinuous activations

Yang, Chao; Huang, Lihong

doi:10.1016/j.neucom.2017.03.017

Cited by 39 publications

(13 citation statements)

References 31 publications

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“…In [28], under FET convergence theory, some FET synchronization criteria of delayed fuzzy neural networks were established. In [29], [30], they discussed the FET problem by employing the same synchronization…”

Section: Introductionmentioning

confidence: 99%

Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying Delays

et al. 2021

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This paper addresses finite-time projective synchronization of stochastic complex-valued neural networks (SCVNNs) with probabilistic time-varying delays (PTVs). First, in the complex domain, PTVs are introduced into the studied model and a novel feedback control scheme is constructed. Next, based on inequalities techniques and the Lyapunov stability approach, some novel projective synchronization criteria are established by decomposing SCVNNs into two equivalent real-valued systems. Moreover, a setting time function is created by employing lemma 4. Compared with previous researches, our theory content is an extension and complement to known results. Finally, numerical simulation is presented to validate the effectiveness of theoretical analysis results. INDEX TERMS Projective synchronization; Finite-time; Probabilistic time-varying delays; Stochastic complex-valued neural networks.

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Section: Introductionmentioning

confidence: 99%

Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying Delays

et al. 2021

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“…Moreover, the finite‐time control techniques have exhibited reliable characteristics. Thus, to better deal with the stability questions, the concept of finite‐time stability emerged . Yang and Huang studied a class of coupled time‐delayed neural networks with discontinuous activations.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, to better deal with the stability questions, the concept of finite-time stability emerged. 5,[16][17][18][19][20][21][22] Yang and Huang 19 studied a class of coupled time-delayed neural networks with discontinuous activations. Liu et al 21 investigated the finite-time synchronization problem for delayed dynamical networks via aperiodically intermittent control.…”

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confidence: 99%

Semiglobal finite‐time synchronization of complex networks with stochastic disturbance via intermittent control

Jiang

et al. 2019

Intl J Robust & Nonlinear

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Summary This paper focuses on the problem of semiglobal finite‐time synchronization of stochastic complex networks via an intermittent control strategy. By establishing a finite‐time criterion condition and a novel finite‐time ℒ‐operator differential inequality, combined with convex techniques, some sufficient conditions are obtained to ensure finite‐time synchronization for stochastic complex networks with time delays. An effective controller is given to guarantee inner finite‐time synchronization, especially for a nondelayed dynamic system. This paper provides a simple controller. Finally, a numerical simulation is given to demonstrate the effectiveness of our results.

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“…We design novel discontinuous controllers and continuous controllers in this paper. When both neuron functions and controllers are discontinuous, there is still a lack of complete theory of synchronization (4) The technique skill and control algorithm are different from those in previous papers (e.g., [20]). We introduce some novel tools such as exponential synchronization theorem, differential inclusion in the sense of Filippov, and generalized Lyapunov approach under a 1-norm framework, and the methods proposed in this paper can be extended to investigate the synchronization of neural network systems…”

Section: Introductionmentioning

confidence: 99%

“…Remark 2. In Proof 2, we choose the linear coupling function φ s = s, without the loss of generality, even if the coupling function becomes more complex such as nonlinear function or coupling delay function; many synchronization criteria for delay dependence were derived under these circumstances [20,27,28]. In the existing literatures, when the neuron functions were discontinuous, the only thing discussed is a single case for either σ = 0 or 0 < σ < 1, respectively.…”

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confidence: 99%

Exponential Synchronization Control of Discontinuous Nonautonomous Networks and Autonomous Coupled Networks

Yang

Huang

2018

Complexity

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This paper concerns complex delayed neural networks with discontinuous activations. Based on the framework of differential inclusion theory, we design two novel controllers by regulating a parameter σ 0≤σ<1 which covers both discontinuous and continuous controllers. Then, we investigate a nonautonomous cellular neural network system and autonomous neural network with linear coupling, respectively. By choosing a time-dependent Lyapunov-Krasovskii functional candidate and suitable controllers, some criteria are studied to guarantee the exponential synchronization of the complex delayed dynamical network. Finally, two numerical examples are given to illustrate our theoretical analysis.

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Finite-time synchronization of coupled time-delayed neural networks with discontinuous activations

Cited by 39 publications

References 31 publications

Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying Delays

Finite-Time Projective Synchronization of Stochastic Complex-Valued Neural Networks With Probabilistic Time-Varying Delays

Semiglobal finite‐time synchronization of complex networks with stochastic disturbance via intermittent control

Exponential Synchronization Control of Discontinuous Nonautonomous Networks and Autonomous Coupled Networks

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