Discrete-time stochastic impulsive BAM neural networks with leakage and mixed time delays: An exponential stability problem |
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| Authors: | C Sowmiya R Raja Jinde Cao X Li G Rajchakit |
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| Institution: | 1. Department of Mathematics, Alagappa University, Karaikudi 630 004, India;2. Ramanujan Centre for Higher Mathematics, Alagappa University, Karaikudi 630 004, India;3. Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, School of Mathematics, Southeast University, Nanjing 211189, China;4. School of Mathematics and Statistics, Shandong Normal University, Ji’nan 250014, China;5. Department of Mathematics, Faculty of Science, Maejo University, Chiang Mai, Thailand;6. School of Electrical Engineering, Nantong University, Nantong 226019, China |
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| Abstract: | In this paper, the stability analysis of impulsive discrete-time stochastic BAM neural networks with leakage and mixed time delays is investigated via some novel Lyapunov–Krasoviskii functional terms and effective techniques. For the target model, stochastic disturbances are described by Brownian motion. Then the result is further extended to address the problem of robust stability of uncertain discrete-time BAM neural networks. The conditions obtained here are expressed in terms of Linear Matrix Inequalities (LMIs), which can be easily checked by MATLAB LMI control toolbox. Finally, few numerical examples are presented to substantiate the effectiveness of the derived LMI-based stability conditions. |
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| Keywords: | Corresponding author |
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