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Event Triggered Finite Time \(H_{\infty }\) Boundedness of Uncertain Markov Jump Neural Networks with Distributed Time Varying Delays

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Abstract

This paper is concerned with the problem of event triggered finite time \(H_{\infty }\) boundedness of uncertain Markov jump neural networks with distributed time varying delays. To reduce the limited network bandwidth, an event triggered scheme is proposed in this paper. The main objective of this paper is to design the event triggered scheme, such that the proposed neural networks have finite time boundedness with admissible uncertainties. The integral terms in the derivative of the Lyapunov–Krasovskii functional are handled by the Wirtinger and Auxillary function based inequality techniques. The proposed conditions are represented by linear matrix inequalities to determine the finite time stability. The advantage of the method in this paper over some existing ones is shown by comparing the results with the existing results. At the end, numerical examples are given to verify the efficiency of the proposed method among them one example was supported by real-life application of the benchmark problem.

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Authors and Affiliations

  1. Department of Mathematics, Thiruvalluvar University, Vellore, Tamil Nadu, 632 115, India

    M. Syed Ali & R. Vadivel

  2. School of Electrical Engineering, Chungbuk National University, Chungdae-ro 1, Cheongju, 28644, Republic of Korea

    O. M. Kwon

  3. Division of Entomology, Department of Zoology, School of Life Sciences, Bharathiar University, Coimbatore, Tamil Nadu, 641 046, India

    Kadarkarai Murugan

  4. Thiruvalluvar University, Vellore, Tamil Nadu, 632 115, India

    Kadarkarai Murugan

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  1. M. Syed Ali
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  2. R. Vadivel
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  3. O. M. Kwon
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  4. Kadarkarai Murugan
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Correspondence to M. Syed Ali.

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The work of the author was supported by CSIR Project No. 25(0274)/17/EMR-II.

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Ali, M.S., Vadivel, R., Kwon, O.M. et al. Event Triggered Finite Time \(H_{\infty }\) Boundedness of Uncertain Markov Jump Neural Networks with Distributed Time Varying Delays. Neural Process Lett 49, 1649–1680 (2019). https://doi.org/10.1007/s11063-018-9895-4

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