Exponential synchronization of stochastic perturbed chaotic delayed neural networks

Sun, Yonghui; Cao, Jinde; Wang, Zidong

doi:10.1016/j.neucom.2006.09.006

Cited by 143 publications

(65 citation statements)

References 30 publications

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“…In the last few years, synchronization in dynamical systems has received a great deal of interest among scientists from various fields [1][2][3][4][5]. In order to better understand the dynamical behaviours of different kind of complex networks, an important and interesting phenomenon to investigate is the synchrony of all dynamical nodes.…”

Section: Introductionmentioning

confidence: 99%

Robust synchronization and fault detection of uncertain master-slave systems with mixed time-varying delays and nonlinear perturbations

Karimi

Luo

2010

2010 Conference on Control and Fault-Tolerant Systems (SysTol)

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In this paper, the problem of robust synchronization and fault detection for a class of masterslave systems subjected to some nonlinear perturbations and mixed neutral and discrete time-varying delays is investigated based on an H ∞ performance condition. By introducing a descriptor technique, using Lyapunov-Krasovskii functional and a suitable change of variables, new required sufficient conditions are established in terms of delay-dependent linear matrix inequalities to synthesize the residual generation scheme. The explicit expression of the synchronization law is derived for the fault such that both asymptotic stability and a prescribed level of disturbance attenuation are satisfied for all admissible nonlinear perturbations. A numerical example with simulation results illustrates the effectiveness of the methodology.

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Section: Introductionmentioning

confidence: 99%

Robust synchronization and fault detection of uncertain master-slave systems with mixed time-varying delays and nonlinear perturbations

Karimi

Luo

2010

2010 Conference on Control and Fault-Tolerant Systems (SysTol)

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“…Chaotic systems are very complex, dynamic nonlinear systems and their response possesses intrinsic characteristics such as broadband noise-like waveforms, prediction difficulty, and sensitivity to initial condition variations, etc. Moreover, many profound theories and methodologies [14][15][16][17][18] have been developed to deal with this issue. For the chaos suppression of permanent magnet synchronous motor OPEN ACCESS systems, some kinds of control design and determination of stability have been conferred [19][20][21][22][23][24][25][26][27][28].…”

Section: Introductionmentioning

confidence: 99%

Finite-Time Chaos Suppression of Permanent Magnet Synchronous Motor Systems

Hou

2014

Entropy

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“…In [25], Mackevicius investigated the synchronization of one dimensional diffusion dynamics, which is an important class of stochastic differential equations. In [30], Sun and Cao provided several sufficient conditions to guarantee the exponential synchronization of two identical chaotic delayed neural networks with stochastic perturbation. Using the adaptive feedback control technique, some sufficient conditions for adaptive synchronization of a class of recurrent neural networks were obtained in [32].…”

Section: Introductionmentioning

confidence: 99%

Adaptive synchronization of chaotic Cohen–Crossberg neural networks with mixed time delays

Zhu

Cao

2010

Nonlinear Dyn

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In this paper, the problem of adaptive synchronization is investigated for a class of CohenCrossberg neural networks with mixed time delays. Based on a Lyapunov-Krasovskii functional and the invariant principle of function differential equations as well as the adaptive control and linear feedback with update law, a linear matrix inequality approach is developed to derive some novel sufficient conditions achieving synchronization of the two coupled networks with mixed time delays. In particular, the mixed time delays in this paper synchronously consist of constant delays, time-varying delays, and distributed delays, which are more general than those discussed in the previous literature. Therefore, the results obtained in this paper comprise and generalize those given in the previous literature. A numerical example and its simulation are provided to show the effectiveness of the theoretical results.

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Exponential synchronization of stochastic perturbed chaotic delayed neural networks

Cited by 143 publications

References 30 publications

Robust synchronization and fault detection of uncertain master-slave systems with mixed time-varying delays and nonlinear perturbations

Robust synchronization and fault detection of uncertain master-slave systems with mixed time-varying delays and nonlinear perturbations

Finite-Time Chaos Suppression of Permanent Magnet Synchronous Motor Systems

Adaptive synchronization of chaotic Cohen–Crossberg neural networks with mixed time delays

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