Sampled-data-based lag synchronization of chaotic delayed neural networks with impulsive control

Zhang, Xiaoyu; Lv, Xiaoxiao; Li, Xiaodi

doi:10.1007/s11071-017-3795-4

Cited by 136 publications

(33 citation statements)

References 35 publications

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“…A large number of chaos synchronization applications in many research fields makes this topic as an important topic in nonlinear systems . These applications grew by introducing fractional version of chaotic systems.…”

Section: Introductionmentioning

confidence: 99%

“…A large number of chaos synchronization applications in many research fields makes this topic as an important topic in nonlinear systems. [1][2][3][4] These applications 5,6 grew by introducing fractional version of chaotic systems. Many fractional-order chaotic systems are introduced such as fractional-order Chua's system, 7 fractional-order Arneodo system, 8 fractional-order Lorenz system, 9 fractional-order Chen system, 10 fractional-order Rössler system, 11 and fractional-order unified system.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive synchronization of new fractional‐order chaotic systems with fractional adaption laws based on risk analysis

Behinfaraz

Ghaemi

Khanmohammadi

2019

Math Methods in App Sciences

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In this paper, a new fractional‐order chaotic system and an adaptive synchronization of fractional‐order chaotic system are proposed. Parameters adaption laws are obtained to design adaptive controllers using Lyapunov stability theory of fractional‐order system. Finally, reliability of designed controllers and risk analysis of adaptive synchronization problem are formulated and, risk of using the proposed controllers in presences of external disturbances are demonstrated. Also, risk of controllers are reduced using an optimizing method. Numerical examples are used to verify the performance of the proposed controllers.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive synchronization of new fractional‐order chaotic systems with fractional adaption laws based on risk analysis

Behinfaraz

Ghaemi

Khanmohammadi

2019

Math Methods in App Sciences

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“…See, for example, [30][31][32][33][34][35] and the references therein. In addition, the impulsive control is found to be very efficient control approach in numerous applied problems [36][37][38][39][40][41][42][43][44].…”

Section: Introductionmentioning

confidence: 99%

Stability of Sets Criteria for Impulsive Cohen-Grossberg Delayed Neural Networks with Reaction-Diffusion Terms

et al. 2019

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The paper proposes an extension of stability analysis methods for a class of impulsive reaction-diffusion Cohen-Grossberg delayed neural networks by addressing a challenge namely stability of sets. Such extended concept is of considerable interest to numerous systems capable of approaching not only one equilibrium state. Results on uniform global asymptotic stability and uniform global exponential stability with respect to sets for the model under consideration are established. The main tools are expansions of the Lyapunov method and the comparison principle. In addition, the obtained results for the uncertain case contributed to the development of the stability theory of uncertain reaction-diffusion Cohen-Grossberg delayed neural networks and their applications. Moreover, examples are given to demonstrate the feasibility of our results.

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“…In general, synchronization means that a system is designed to simulate the dynamic behavior of another system, that is, the state trajectory of two systems is finally identical. Therefore, many important results on synchronization have been obtained in the last few years [17][18][19][20], and various control strategies have been developed to design effective controllers for achieving synchronization, such as adaptive control [21], pinning control [22], feedback control [23], impulsive control [24][25][26][27], and intermittent control [28].…”

Section: Introductionmentioning

confidence: 99%

Exponential Synchronization of Neural Networks via Feedback Control in Complex Environment

Cao

et al. 2018

Complexity

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The problem of exponential synchronization for neural networks is investigated via feedback control in complex environment. By constructing suitable Lyapunov-Krasovskii functionals and applying the piecewise analytic method, some sufficient criteria for exponential synchronization of the addressed neural networks are established in terms of linear matrix inequalities (LMIs). The feedback control in complex environment includes the delayed aperiodically intermittent control and dynamic output feedback control. Moreover, the delayed aperiodically intermittent dynamic output feedback controller is designed based on the established LMIs. A numerical example and its numerical simulations are finally presented to show the effectiveness of obtained theoretical results.

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Sampled-data-based lag synchronization of chaotic delayed neural networks with impulsive control

Cited by 136 publications

References 35 publications

Adaptive synchronization of new fractional‐order chaotic systems with fractional adaption laws based on risk analysis

Adaptive synchronization of new fractional‐order chaotic systems with fractional adaption laws based on risk analysis

Stability of Sets Criteria for Impulsive Cohen-Grossberg Delayed Neural Networks with Reaction-Diffusion Terms

Exponential Synchronization of Neural Networks via Feedback Control in Complex Environment

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