Synchronization of CVNNs: A Time-Scale Impulsive Strategy

Abstract

In this paper, we mainly investigate global exponential synchronization for master-slave complex-valued neural networks (CVNNs) under a time-scale impulsive strategy. CVNNs are separated into real and imaginary parts, which lead to two real-valued neural networks (RVNNs). Firstly, impulsive Halanay differential inequality on time scales as well as the comparison between general exponential function and exponential function in timescale sense is given based on the calculus of time scales. Then by constructing the appropriate Lyapunov functional and using the established lemma and proposition, the concepts of average impulsive interval (AII) and average impulsive gain (AIG), some novel synchronization criteria for the given master-slave CVNNs in impulsive form are obtained. Additionally, the convergence rate is estimated explicitly. Finally, one numerical example is given to show the effectiveness of the proposed results.

Keywords

• Complex-valued neural networks
• exponential synchronization
• impulsive control
• Halanay differential inequality
• time scale