Adaptive hybrid projective synchronization of two coupled fractional-order complex networks with different sizes

Ma, Tiedong; Zhang, Jun; Zhou, Youfu; Wang, Haoyang

doi:10.1016/j.neucom.2015.02.071

Cited by 28 publications

(5 citation statements)

References 44 publications

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“…After that, several control schemes have been developed to synchronize the behavior of the chaotic systems. Active method [20,26], adaptive method [1,9,18,42], impulsive method [13], projective method [6,32], lag method [27], sliding mode method [2,30], linear feedback control [33] and backstepping control method [41] are some of the prevalent synchronization methods.…”

Section: Doi: 1014736/kyb-2018-4-0829mentioning

confidence: 99%

“…Theorem 3.1. For the given leader unified TSUCS system (6), the follower unified Lü system (15), the state variable error and parameter error (17) and their corresponding dynamical equations (18), and for any initial values, the motion trajectories of the follower system tracks the trajectories of the leader system if the feedback control input and estimated update law of the follower system parameter α satisfy:…”

Section: Non-identical Tsucs Synchronization Problemmentioning

confidence: 99%

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Chaos synchronization of TSUCS unified chaotic system, a modified function projective control method

Tirandaz¹

2018

Kybernetika

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Section: Doi: 1014736/kyb-2018-4-0829mentioning

confidence: 99%

Section: Non-identical Tsucs Synchronization Problemmentioning

confidence: 99%

Chaos synchronization of TSUCS unified chaotic system, a modified function projective control method

Tirandaz¹

2018

Kybernetika

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“…For these reasons, substantial effort has been expended in the study of adaptive control for FONNs [27]- [30]. In [31], the authors investigated the hybrid projective synchronization of fractional-order two coupled complex dynamical networks with different sizes by adaptive control. Moreover, adaptive control can guarantee stability in complex dynamical networks and can appropriately tune the strengths of the interconnections among network nodes [32], [33].…”

Section: Introductionmentioning

confidence: 99%

Synchronization Analysis of Fractional-Order Neural Networks With Adaptive Intermittent-Active Control

et al. 2022

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This paper concentrates on the study of adaptive control for the synchronization of fractional-order neural networks. Instead of classical adaptive control updating method, an intermittent-active updating strategy is proposed to adaptively tune the control gain in a fractional-order fashion. Moreover, quantization is brought into the control design to take into account the restricted bandwidth in signal transmission. Note that the suggested controller is basic yet effective in terms of the fractional-order system. The main theorem is established with the method of reduction to absurdity as well as Lyapunov stability theorem. Finally, simulation calculation is conducted to validate the effectiveness of our proposed method.

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“…Since the pioneering work done by Ott et al (1990) at 1990 on chaotic systems, several methods have been investigated on synchronization of two chaotic or hyper-chaotic systems. Active method Nik et al (2014), Richter (2002), Huang and Cao (2017), Adaptive method Adloo and Roopaei (2011), Tirandaz-Hajipour (2017), Ma et al (2015), Hong (2013), impulsive method Li et al (2005), projective method Chun-Lai et al (2016), Tirandaz and Karmi-Mollaee (2017), lag method Rosenblum et al (1997), sliding method Sun et al (2014), Aghababa and Heydari (2012) and backstepping control method Yu et al (2011) are some of the investigated synchronization methods. scrambling technique.…”

Section: Introductionmentioning

confidence: 99%

On active synchronization of fractional-order Bloch chaotic system and its practical application in secure image transmission

Tirandaz

Karami-Mollaee

2018

IJICC

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Purpose The purpose of this paper is to propose a novel and secure image transmission based on the unpredictable behavior of the chaotic systems. Design/methodology/approach The proposed approach includes two main contributions: synchronization scheme and transmission scheme. The synchronization scheme benefits the advantage of the fractional-order active synchronization method. A new control law is derived to asymptotically synchronize the underlined fractional-order Bloch chaotic system. The validity of the proposed synchronization scheme is proved by the Lyapunov stability theorem. Then, a novel image transmission scheme is designed to transfer image data via chaotic signals, which modulates the encrypted data in the sender signals and demodulates it at the receiver side. Findings Numerical simulations are provided to show the validity and effectiveness of the proposed image transmission system. Furthermore, the performance of the image transmission system is evaluated using some illustrative examples and their corresponding statistical tests. The results demonstrate the effectiveness of the proposed method in comparison with other proposed methods in this subject. Originality/value A new chaos-based image transmission system is developed based on the synchronization of Bloch chaotic system. The introduced transmission system is interesting and could be applicable to any kind of secure image/video transmission.

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Adaptive hybrid projective synchronization of two coupled fractional-order complex networks with different sizes

Cited by 28 publications

References 44 publications

Chaos synchronization of TSUCS unified chaotic system, a modified function projective control method

Chaos synchronization of TSUCS unified chaotic system, a modified function projective control method

Synchronization Analysis of Fractional-Order Neural Networks With Adaptive Intermittent-Active Control

On active synchronization of fractional-order Bloch chaotic system and its practical application in secure image transmission

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