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Extended Dissipative Criteria for Generalized Markovian Jump Neural Networks Including Asynchronous Mode-Dependent Delayed States

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Abstract

This study scrutinizes the extended dissipative problem for Markovian jump generalized neural networks with asynchronous mode-dependent time-varying interval delayed states. A suitable Lyapunov–Krasovskii functional and a new bounding technique can derive delay-dependent results to achieve an extended dissipative performance index. Jensen’s inequality, reciprocally convex combination, and a novel integral inequality technique are utilized in this paper. The proposed criteria are reliable since many components are included in the unified neural network model, Markovian jumping, and time-varying delay with asynchronous modes. In this work, the systemic and time-varying delay modes are expressed asynchronously, which means that they depend on different jumping modes. Four numerical examples show the effectiveness and usefulness of the presented results.

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Authors and Affiliations

  1. Graduate School of Advanced Science and Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, 739-8527, Japan

    Ramasamy Saravanakumar

  2. Department of Mathematics, Thiruvalluvar University, Vellore, Tamil Nadu, 632115, India

    M. Syed Ali

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  1. Ramasamy Saravanakumar
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  2. M. Syed Ali
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This work was supported by Grant-in-Aid for Research Activity Start-up No. 20K23328, funded by Japan Society for the Promotion of Science (JSPS).

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Saravanakumar, R., Ali, M.S. Extended Dissipative Criteria for Generalized Markovian Jump Neural Networks Including Asynchronous Mode-Dependent Delayed States. Neural Process Lett 54, 1623–1645 (2022). https://doi.org/10.1007/s11063-021-10697-2

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