Synchronization in finite-/fixed-time of delayed diffusive complex-valued neural networks with discontinuous activations

In this paper, we analyze the finite-time synchronization problem between two delayed diffusive complex-valued neural networks(CVNNs) with discontinuous activations. We first establish the threshold finite-/fixed-time synchronization(FFTS) dynamics of the model by designing a novel negative exponent controller. Then we further study the finite-time synchronization via the adaptive control scheme. Some novel and useful finite-time synchronization criteria are established based on the discontinuous version of finite-time convergence theorem and Filippov regularization techniques, the upper-bound of the settling time is explicitly estimated as well. The obtained results extend some previous ones on CVNNs. Moreover, numerical simulations are performed to substantiate the effectiveness of the theoretical analysis. (C) 2020 Elsevier Ltd. All rights reserved.

Automated summary

This paper investigates the finite-time synchronization problem between two delayed and diffusive complex-valued neural networks with discontinuous activations. By designing a negative exponent controller and an adaptive control scheme, novel and useful finite-time synchronization criteria are established with an explicit estimation of the upper-bound of the settling time. The effectiveness of the theoretical analysis is substantiated through numerical simulations.