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A neural-network-based exponential synchronisation for chaotic secure communication via improved genetic algorithm

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  • Feng-Hsiag Hsiao

Abstract

In this study, a novel approach via improved genetic algorithm (IGA)-based fuzzy observer is proposed to realise exponential optimal H∞ synchronisation and secure communication in multiple time-delay chaotic (MTDC) systems. First, an original message is inserted into the MTDC system. Then, a neural-network (NN) model is employed to approximate the MTDC system. Next, a linear differential inclusion (LDI) state-space representation is established for the dynamics of the NN model. Based on this LDI state-space representation, this study proposes a delay-dependent exponential stability criterion derived in terms of Lyapunov's direct method, thus ensuring that the trajectories of the slave system approach those of the master system. Subsequently, the stability condition of this criterion is reformulated into a linear matrix inequality (LMI). Due to GA's random global optimisation search capabilities, the lower and upper bounds of the search space can be set so that the GA will seek better fuzzy observer feedback gains, accelerating feedback gain-based synchronisation via the LMI-based approach. IGA, which exhibits better performance than traditional GA, is used to synthesise a fuzzy observer to not only realise the exponential synchronisation, but also achieve optimal H∞ performance by minimizing the disturbance attenuation level and recovering the transmitted message. Finally, a numerical example with simulations is given in order to demonstrate the effectiveness of our approach.

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  • Feng-Hsiag Hsiao, 2016. "A neural-network-based exponential synchronisation for chaotic secure communication via improved genetic algorithm," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(13), pages 3149-3166, October.
    • Handle: RePEc:taf:tsysxx:v:47:y:2016:i:13:p:3149-3166
    DOI: 10.1080/00207721.2015.1100348
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    References listed on IDEAS

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    1. Sun, Yeong-Jeu, 2009. "Exponential synchronization between two classes of chaotic systems," Chaos, Solitons & Fractals, Elsevier, vol. 39(5), pages 2363-2368.
    2. Karimi, Hamid Reza & Maass, Peter, 2009. "Delay-range-dependent exponential H∞ synchronization of a class of delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1125-1135.
    3. Lin, Shih-Lin & Tung, Pi-Cheng, 2009. "A new method for chaos control in communication systems," Chaos, Solitons & Fractals, Elsevier, vol. 42(5), pages 3234-3241.
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