A new method for exponential synchronization of memristive recurrent neural networks

作者：Zhang, Ruimei; Park, Ju H.^*; Zeng, Deqiang; Liu, Yajuan; Zhong, Shouming

来源：Information Sciences, 2018, 466: 152-169.

DOI：10.1016/j.ins.2018.07.038

• Exponential synchronization
• Memristive recurrent neural networks
• Switching matrix approach

This paper investigates the exponential synchronization problem of memristive recurrent neural networks (MRNNs). A novel approach, switching matrix approach, is considered to study synchronization of MRNNs for the first time. All the matrices in the constructed Lyapunov-Krasovskii functional (LKF) are switching according to different switching rules. Based on the switching matrix approach, a new synchronization criterion is established in the form of linear matrix inequalities (LMIs). Compared with some existing methods, the switching matrix approach is more flexible and can improve the synchronization performance with low control cost. Finally, numerical simulations are provided to show the effectiveness and advantages of the proposed results.

• 出版日期2018-10
• 单位华北电力大学; 内江师范学院; 华北电力大学（保定）; 电子科技大学