Exponential synchronization of stochastic chaotic neural networks with mixed time delays and Markovian switching

Zheng, Cheng‐De; Zhang, Huaguang; Wang, Zhanshan

doi:10.1007/s00521-013-1507-7

Cited by 13 publications

(7 citation statements)

References 26 publications

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“…As far as the authors know, there are many achievements on exponential synchronization of switched neural networks with mixed delays, such as [61]- [63]. Note that, the state feedback controllers in [61], [62] and the adaptive controller in [63] need to be continuously updated, while the event-triggering controller (10) only needs to be updated at discrete instants which can effectively reduce the control cost.…”

Section: Remarkmentioning

confidence: 99%

Exponential Synchronization of Switched Neural Networks With Mixed Time-Varying Delays via Static/Dynamic Event-Triggering Rules

2020

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This paper is devoted to the exponential synchronization of switched neural networks with mixed time-varying delays via static/dynamic event-based rules. At first, by introducing an indicator function, the switched neural networks are transformed into neural networks with general form. Then, sufficient conditions are deduced to achieve exponential synchronization for drive-response systems by two different types of event-triggering rules, i.e., static and dynamic event-triggering rules. Meanwhile, we can ensure that the Zeno phenomenon does not occur by proving that the time interval between two successive trigger events has a positive lower bound. Finally, two illustrative examples are elaborated to substantiate the theoretical results. INDEX TERMS Switched neural network, exponential synchronization, event-based control, time-varying delay, distributed delay.

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Section: Remarkmentioning

confidence: 99%

Exponential Synchronization of Switched Neural Networks With Mixed Time-Varying Delays via Static/Dynamic Event-Triggering Rules

2020

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“…In addition, chaotic systems may be stable or unstable through some random inputs. These types of chaotic systems have been extensively investigated …”

Section: Introductionmentioning

confidence: 99%

Exponential synchronization of chaotic systems with stochastic noise via periodically intermittent control

Tong

Chen

et al. 2020

Intl J Robust & Nonlinear

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The problem of second-moment exponential synchronization is discussed for chaotic systems. Different from some existing results, a unified drive-response system is formulated, which involves stochastic noise and the time-varying delay. Meanwhile, the feedback controller is presented by the periodically intermittent control. By exploiting the Lyapunov stability theory, the improved reciprocally convex inequality and the Itô formula, several new sufficient conditions are obtained to make two systems synchronized. In addition, the controller is determined by the control period and the control width. Finally, simulation results illustrate that the designed controller achieves the desired performance. K E Y W O R D Schaotic systems, exponential synchronization, periodically intermittent control, stochastic noise, unified model 1 In the past years, the stabilization and synchronization of chaotic systems have gained much attention among researchers owing to its wide applications in many areas, 1-5 such as economics, secure communications, and biological sciences.As is known to all, chaotic systems have high nonlinear dynamic characteristics and strong randomness, and it is Abbreviations: ANA, antinuclear antibodies; APC, antigen-presenting cells; IRF, interferon regulatory factor. Int J Robust Nonlinear Control. 2020;30:2611-2624.wileyonlinelibrary.com/journal/rnc

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“…In recent years, the analysis for complex networks with Markovian switching have been extensively studied. [19][20][21][22][23][24] It should be noticed that most of literature only focus on complex networks with Markovian switching parameters (see References 19,20 and the references therein). Few literature consider complex networks with Markovian switching topologies, but every switching subnetwork topology is required to contain a directed spanning tree or be strongly connected, which may be conservative.…”

Section: Introductionmentioning

confidence: 99%

“…Fortunately, Markovian switching systems can describe such changes. In recent years, the analysis for complex networks with Markovian switching have been extensively studied 19‐24 . It should be noticed that most of literature only focus on complex networks with Markovian switching parameters (see References 19,20 and the references therein).…”

Section: Introductionmentioning

confidence: 99%

Exponential bipartite synchronization of random signed networks with Markovian switching via impulsive control

Wang

Xie

2020

Intl J Robust & Nonlinear

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In this article, exponential bipartite synchronization in mth moment of random signed networks is studied. Different from previous work, both random disturbances and Markovian switching are considered into signed networks. It is worth emphasizing that the topological structure of signed networks depends on Markovian switching, and not all switching subnetworks are required to be strongly connected. In addition, an impulsive controller is designed to make random signed networks with Markovian switching achieve bipartite synchronization. Then, by using Lyapunov method and signed digraph theory, two synchronization criteria are obtained. These criteria have a close relationship with the topological structure of signed networks, the impulsive gain and the reverse average impulsive interval. Furthermore, our theoretical results are applied to studying exponential bipartite synchronization in mth moment of single-link robot arms in engineering, and a synchronization criterion is given. Finally, some numerical simulations are shown to illustrate the effectiveness and feasibility of theoretical results.

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Exponential synchronization of stochastic chaotic neural networks with mixed time delays and Markovian switching

Cited by 13 publications

References 26 publications

Exponential Synchronization of Switched Neural Networks With Mixed Time-Varying Delays via Static/Dynamic Event-Triggering Rules

Exponential Synchronization of Switched Neural Networks With Mixed Time-Varying Delays via Static/Dynamic Event-Triggering Rules

Exponential synchronization of chaotic systems with stochastic noise via periodically intermittent control

Exponential bipartite synchronization of random signed networks with Markovian switching via impulsive control

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