Stability analysis of almost periodic solutions of discontinuous BAM neural networks with hybrid time-varying delays and D operator |
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| Authors: | Fanchao Kong Quanxin Zhu Kai Wang Juan J Nieto |
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| Institution: | 1. School of Mathematics and Statistics, Anhui Normal University, Wuhu, Anhui 241000, China;2. School of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao 266061, China;3. Key Laboratory of HPC-SIP (MOE), College of Mathematics and Statistics, Hunan Normal University, Changsha 410081, Hunan, China;4. School of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, China;5. Instituto de Matemáticas, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain |
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| Abstract: | In the paper, we are concerned with a class of discontinuous BAM neural networks with hybrid time-varying delays and D operator. Based on the concept of Filippov solution, by means of the differential inclusions theory and the non-smooth analysis theory with Lyapunov-like approach, some new and novel sufficient conditions are derived to guarantee the existence, uniqueness and global exponential stability of almost-periodic solution of our proposed neural network model. To the authors’ knowledge, the results established in the paper are the only available results on the BAM neural networks, connecting the three main characteristics, i.e., discontinuous activation functions, hybrid time-varying delays and D operator. Some previous works in the literature are significantly extend and complement. Finally, two topical simulation examples are given to show the effectiveness of the established main results. |
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| Keywords: | Corresponding author at: School of Mathematics and Statistics Anhui Normal University Wuhu Anhui 241000 China |
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