Xia Huang

TL;DR: This study addresses the problem of quasi-synchronisation of fractional-order memristor-based neural networks (FMNNs) with time delay in the presence of parameter mismatches with linear state feedback combined with delayed state feedback control law, which guarantees that for a predetermined synchronisation error bound, quasi- synchronisation of two FMNNs with mismatched parameters will be achieved.

TL;DR: The objective is to design an asynchronous output feedback controller, which ensures that the closed-loop system is generalised stochastically dissipative, which covers not only the asynchronous controller but also the mode-independent one.

TL;DR: In this paper, the stability analysis and state estimation of Markov jump static neural networks subject to time delays by the feat of Bessel-Legendre inequality are investigated, and an enhanced Lyapunov-Krasovskii functional suitable for the canonical Bessel -legendre inequality is constructed.

TL;DR: The main objective is centred on designing a reliable mode-dependent filter which can ensure that the resulting filtering error system is exponentially admissible and simultaneously satisfies the extended dissipative property in the presence of sensor failures.

TL;DR: The authors' purpose is to design a filter that ensures the error system is extended stochastically dissipative and with the aid of the Lyapunov stability theory and linear matrix inequality approach, a set of ϵ -independent conditions are derived to obtain the filter gains.