This draft addresses the exponential stability problem for semi-Markovian jump generalized neural networks (S-MJGNNs) with interval time-varying delays. The exponential stability conditions are derived by establishing a suitable Lyapunov-Krasovskii functional and applying new analysis method. Improved results are obtained to guarantee the exponential stability of S-MJGNNs through improved reciprocally convex combination and new weighted integral inequality techniques. The method in this paper shows the advantages over some existing ones. To verify the advantages and benefits of employing proposed method is explained through numerical examples.
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Hebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Peoples R ChinaHebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Peoples R China
Qiu, Jiqing
Lu, Kunfeng
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Hebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Peoples R ChinaHebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Peoples R China
Lu, Kunfeng
Shi, Peng
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Univ Glamorgan, Fac Adv Technol, Pontypridd CF37 1DL, M Glam, Wales
Victoria Univ, Sch Sci & Engn, Melbourne, Vic 8001, AustraliaHebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Peoples R China
Shi, Peng
Mahmoud, Magdi S.
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King Fahd Univ Petr & Minerals, Dept Syst Engn, Dhahran 31261, Saudi ArabiaHebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Peoples R China