Global asymptotic stability is an important issue for wide applications of recurrent neural
networks with time-varying delays. The Lyapunov–Krasovskii functional method is a …

Neuronal state estimation of neural networks is a fundamental issue, aiming at estimating
neuronal states from contaminated neural measurement outputs. Inspired by extensive …

This article deals with H∞ state estimation of neural networks with mixed delays. In order to
make full use of delay information, novel delay-product Lyapunov-Krasovskii functional …

This work investigates L2-L∞ filtering problem for a class of stochastic systems with time-
delay and randomly occurring phenomena. The purpose of the addressed problem is to …

This article is concerned with the energy-to-peak state estimation problem for a class of
linear discrete-time systems with energy-bounded noises and intermittent measurement …

Suppressing torsional vibration of drill-string has great safety and economic importance to
drilling process. Note that most existing control methods only measure surface information …

In this paper, the protocol-based remote state estimation problem is considered for a kind of
delayed artificial neural networks. The random time-varying delays fall into certain intervals …

In this paper, the H∞ state estimation problem is studied for a class of multi-rate artificial
neural networks with integral measurements. A novel method, rather than the widely used …

This paper is concerned with observer‐based trajectory control of directional drilling system
with rotary steering devices. Since the trajectory orientation cannot be measured directly …

This paper deals with the global exponential stability problem of neural networks with time-
varying delay. A novel Lyapounov–Krasovskii functional (LKF), which contains a common …