Non-fragile H-infinity synchronization of memristor-based neural networks using passivity theory

作者：Mathiyalagan K; Anbuvithya R; Sakthivel R; Park Ju H; Prakash P

来源：Neural Networks, 2016, 74: 85-100.

DOI：10.1016/j.neunet.2015.11.005

• Memristor
• Recurrent neural networks
• Random uncertainties
• Non-fragile control
• Uncertain delay

In this paper, we formulate and investigate the mixed H-infinity and passivity based synchronization criteria for memristor-based recurrent neural networks with time-varying delays. Some sufficient conditions are obtained to guarantee the synchronization of the considered neural network based on the master-slave concept, differential inclusions theory and Lyapunov-Krasovskii stability theory. Also, the memristive neural network is considered with two different types of memductance functions and two types of gain variations. The results for non-fragile observer-based synchronization are derived in terms of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed criterion is demonstrated through numerical examples.

• 出版日期2016-2