Anbuvithya, R., Dheepika Sri, S., Vadivel, R., Hammachukiattikul, P., Park, Choonkil, Nallappan, Gunasekaran. (1400). Extended dissipativity synchronization for Markovian jump recurrent neural networks via memory sampled-data control and its application to circuit theory. هنرهای کاربردی, 13(1), 2801-2820. doi: 10.22075/ijnaa.2021.25114.2919
R. Anbuvithya; S. Dheepika Sri; R. Vadivel; P. Hammachukiattikul; Choonkil Park; Gunasekaran Nallappan. "Extended dissipativity synchronization for Markovian jump recurrent neural networks via memory sampled-data control and its application to circuit theory". هنرهای کاربردی, 13, 1, 1400, 2801-2820. doi: 10.22075/ijnaa.2021.25114.2919
Anbuvithya, R., Dheepika Sri, S., Vadivel, R., Hammachukiattikul, P., Park, Choonkil, Nallappan, Gunasekaran. (1400). 'Extended dissipativity synchronization for Markovian jump recurrent neural networks via memory sampled-data control and its application to circuit theory', هنرهای کاربردی, 13(1), pp. 2801-2820. doi: 10.22075/ijnaa.2021.25114.2919
Anbuvithya, R., Dheepika Sri, S., Vadivel, R., Hammachukiattikul, P., Park, Choonkil, Nallappan, Gunasekaran. Extended dissipativity synchronization for Markovian jump recurrent neural networks via memory sampled-data control and its application to circuit theory. هنرهای کاربردی, 1400; 13(1): 2801-2820. doi: 10.22075/ijnaa.2021.25114.2919

Extended dissipativity synchronization for Markovian jump recurrent neural networks via memory sampled-data control and its application to circuit theory

International Journal of Nonlinear Analysis and Applications
مقاله 229، دوره 13، شماره 1، خرداد 2022، صفحه 2801-2820    اصل مقاله (559.04 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.25114.2919
نویسندگان
R. Anbuvithya1؛ S. Dheepika Sri1؛ R. Vadivel* 2؛ P. Hammachukiattikul2؛ Choonkil Park3؛ Gunasekaran Nallappan4
1Department of Mathematics, Sri Sarada College for Women (Autonomous), Salem 636016, India
2Department of Mathematics, Faculty of Science and Technology, Phuket Rajabhat University, Phuket-83000, Thailand
3Research Institute of Natural Science, Hanyang University, Seoul 04763, Korea
4Intelligence Laboratory, Toyota Technological Institute, Nagoya, 468-8511, Japan
چکیده
 The problem of synchronization with extended dissipativity for Markovian Jump Recurrent Neural Networks (MJRNNs) is investigated. For MJRNNs, a new memory sampled-data extended dissipative control approach is suggested here. Some sufficient conditions in terms of Linear Matrix Inequalities (LMIs) are acquired by suitably establishing a relevant Lyapunov - Krasovskii functional (LKF), wherein the master and the slave system of MJRNNs are quadratically stable. At last, a numerical section is provided, along with one of the applications in circuit theory that clearly illustrates the efficacy of the proposed method's performance.
کلیدواژه‌ها
Extended Dissipativity؛ Markovian Jump Recurrent Neural Networks؛ Memory Sampled data control؛ Synchronization
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