Periodic oscillation of memristor-based recurrent neural networks with time-varying delays and leakage delays

Abstract

PurposeThe purpose of this paper is to investigate the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.Design/methodology/approachThe differential inequality theory and some novel mathematical analysis techniques are applied.FindingsA set of sufficient conditions which guarantee the existence and global exponential stability of periodic solution of involved model is derived.Practical implicationsIt plays an important role in designing the neural networks.Originality/valueThe obtained results of this paper are new and complement some previous studies. The innovation of this paper concludes two aspects: the analysis on the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays is first proposed; and it is first time to establish the sufficient criterion which ensures the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.