Finite-time synchronization of delayed memristive neural networks via 1-norm-based analytical approach

Abstract

By using 1-norm-based analytical approach, this paper considers finite-time (FET) synchronization for memristive neural networks (MNNs) with time-varying delays. New quantized controllers are designed, which can save communication channel and play an important role in synchronizing MNNs. By constructing Lyapunov function, and developing 1-norm-based analytical methods, several conditions are derived to guarantee that the MNNs can be synchronized within a settling time. In addition, the settling time is also presented for the considered MNNs. Some numerical simulations are provided to illustrate the theoretical results.