On State Estimation for Discrete Time-Delayed Memristive Neural Networks Under the WTOD Protocol: A Resilient Set-Membership Approach

In this article, a resilient set-membership approach is put forward to deal with the state estimation problem for sort of discrete-time memristive neural networks (DMNNs) hybrid time delays under weighted try-once-discard protocol (WTODP). The WTODP utilized mitigate unnecessary network congestion occurring in channel between DMNNs and estimator. order ensure resilience against possible realization errors, estimator gain permitted undergo some norm-bounded parameter drifts. Our objective design (RSME) that capable resisting variations unknown-but-bounded noises by confining error certain ellipsoidal regions. By resorting recursive matrix inequality technique, sufficient conditions are acquired existence expected RSME and, subsequently, an optimization formalized minimizing constraint ellipsoid (with respect error) WTODP. Finally, numerical simulation carried out validate usefulness RSME.