Title of article
Extended dissipativity synchronization for Markovian jump recurrent neural networks via memory sampled-data control and its application to circuit theory
Author/Authors
Anbuvithya, R. Department of Mathematics - Sri Sarada College for Women (Autonomous), Salem, India , Dheepika Sri, S. Department of Mathematics - Sri Sarada College for Women (Autonomous), Salem, India , Vadivel, R. Department of Mathematics - Faculty of Science and Technology -Phuket Rajabhat University, Phuket, Thailand , Hammachukiattikul, P. Department of Mathematics - Faculty of Science and Technology -Phuket Rajabhat University, Phuket, Thailand , Park, Choonkil Research Institute of Natural Science - Hanyang University, Seoul, Korea , Nallappan, Gunasekaran Intelligence Laboratory - Toyota Technological Institute, Nagoya, Japan
Pages
20
From page
2801
To page
2820
Abstract
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.
Keywords
Extended Dissipativity , Markovian Jump Recurrent Neural Networks , Memory Sampled data control , Synchronization
Journal title
International Journal of Nonlinear Analysis and Applications
Serial Year
2022
Record number
2713926
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