Document Type : Research Paper

Authors

• R. Anbuvithya ¹
• S. Dheepika Sri ¹
• R. Vadivel ²
• P. Hammachukiattikul ²
• Choonkil Park ³
• Gunasekaran Nallappan ⁴

¹ Department of Mathematics, Sri Sarada College for Women (Autonomous), Salem 636016, India

² Department of Mathematics, Faculty of Science and Technology, Phuket Rajabhat University, Phuket-83000, Thailand

³ Research Institute of Natural Science, Hanyang University, Seoul 04763, Korea

⁴ Intelligence Laboratory, Toyota Technological Institute, Nagoya, 468-8511, Japan

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