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In this paper, adaptive fixed-time synchronization(FTS) of stochastic memristor-based neural networks(MNNs) with discontinuous activations and mixed delays is investigated. Both continuous and discontinuous activation functions are discussed for stochastic MNNs. Meanwhile, a feedback control strategy and a new adaptive control strategy are proposed to ensure FTS of stochastic MNNs. Since the MNNs are right-hand discontinuous systems, the set-valued mapping and differential inclusion theory are used to deal with its discontinuity. Synchronization criteria and the settling time (ST) are obtained with the aid of some lemmas and mathematical inequalities under corresponding control schemes. It's worth noting that the ST can be adjusted to desired value by controller parameters regardless of the initial values. Finally, the feasibility of theoretical results are proved via simulation results. [ABSTRACT FROM AUTHOR]

This paper focuses on the problem of H ∞ performance synchronization for a class of Takagi-Sugeno(T-S) fuzzy complex networks with hybrid coupling delays. The hybrid delays consider discrete-time coupling delay, partial coupling delay and distributed coupling delay. First, the pinning control strategy related to distributed coupling, discrete-time coupling delay is considered for the first time. Besides, by adopting multiple integral Lyapunov functional, with a decoupling approach and auxiliary function-based integral inequality and mathematical techniques, a less conservation condition can be obtained to guarantee that the T-S fuzzy complex networks can achieve the H ∞ synchronization with hybrid coupling delays by a non-fragile delay-dependent pinning controller. At last, two simulation examples are purposed to prove the availability of the obtained result. [ABSTRACT FROM AUTHOR]