This paper is concerned with quasi-synchronization of delayed memristive neural networks (MNNs) with switching jumps mismatches via aperiodically intermittent control. The issue is presented for three reasons: 1) the existing controllers for synchronization may be too complicated and not economical; 2) under the influence of switching jumps mismatches, synchronization of MNNs may fail to achieve; and 3) matrix measure method is less conservative but cannot be applied directly to synchronization of MNNs. To overcome these difficulties, the concept of asynchronously switching time interval is proposed to describe the phenomenon when the drive-response MNNs switch their connection weights asynchronously. Then, aperiodically intermittent control is designed and quasi-synchronization analysis is carried out based on a combined method that compromises the merits of interval matrix method and matrix measure method. A quasi-synchronization criterion, expressed in terms of the mixture of p-norm and matrix measure of the memristive connection weights, is established. Meanwhile, the fundamental reason for the failure of complete synchronization is revealed. Moreover, an explicit expression of the error level is obtained and the design of the controller under a predetermined error level is presented. The obtained results in this paper reduce the conservativeness and provide a novel insight into the research of synchronization of MNNs.

In this article, a memory-based event-trigger (MBET) scheme is designed to investigate the global synchronization problem of a class of Lur’e systems. There are two reasons for presenting this issue: 1) most of the existing event-trigger schemes do not take the historical state information into account and, therefore, may have some conservatism in reducing the number of triggering times and 2) the existing Lyapunov functionals cannot be directly utilized in the stability analysis of the resulting closed-loop system in this article. Motivated by the above-mentioned considerations, an MBET scheme, in which a time-memory term and an exponential decaying term are incorporated into the threshold function, is newly designed. It is beneficial to enlarging the intertrigger intervals and, thus, can further reduce the transmission of sampled data packets. Taking the features of MBET into consideration, a novel piecewise but continuous functional is constructed. On this basis, Lyapunov stability theory and some inequality estimation techniques are used to develop three linear matrix inequalities (LMIs)-based synchronization criteria and, meanwhile, a co-design for the control gain and the triggering matrix is carried out. Finally, some comparative analyses are provided to demonstrate the advantages of the MBET through an example of Chua’s circuit. Also, the application to information safety is given to verify the effectiveness of the synchronization results by using a 3-neuron neural network.

This article addresses the quasi-synchronization problem of delayed memristive neural networks (MNNs) via hybrid event-triggered control. First, a hybrid event-triggering mechanism with a novel threshold function is devised. Therein, an exponential decay term and a non-negative constant term are additionally introduced. It can further extend the time span between two successively triggered events and therefore can reduce the amount of triggering times in comparison with some existing event-triggering mechanisms. Then, by constructing a time-dependent and piecewise Lyapunov functional, a less conservative criterion for quasi-synchronization of drive-response delayed MNNs is formulated in terms of linear matrix inequalities. In addition, an explicit expression of the error bound is provided and the design of the feedback gain is presented for a predetermined error bound. Finally, a numerical example is given to demonstrate the effectiveness of the theoretical analysis and the advantages of the proposed event-triggering scheme.