LAUSR

Abstract This work studies lag quasi-synchronization (LQS) for discrete-time master–slave (MS) periodic neural networks (NNs) with the communication channel (CC) constraint. A logarithmic quantizer is used to overcome the CC constraint, and a redundant CC is introduced to transmit more information to improve the system performance. Two independent bernoulli processes are considered to model the packet dropouts of the main and the redundant CCs, respectively. A sufficient condition, ensuring LQS of MS NNs, is achieved, which also gives the boundary of the LQS error. Finally, a controller is designed on the basis of the obtained sufficient condition and the derived result is proved by a numerical example.