This paper presents a review of the central theories involved in hybrid models based on
fuzzy systems and artificial neural networks, mainly focused on supervised methods for …

This paper investigates the issue of the reliable asynchronous sampled-data filtering of
Takagi–Sugeno (T–S) fuzzy delayed neural networks with stochastic intermittent faults …

The event-triggered sliding-mode control (SMC) for discrete-time networked Markov jum**
systems (MJSs) with channel fading is investigated by means of a genetic algorithm. In order …

This article focuses on the design, test, and validation of a deep neural network (DNN)-
based control scheme capable of predicting optimal motion commands for autonomous …

This paper investigates the problem of fault detection for nonlinear discrete-time networked
systems under an event-triggered scheme. A polynomial fuzzy fault detection filter is …

In this study, asynchronous sliding-mode control (SMC) for discrete-time networked hidden
stochastic jump systems subjected to the semi-Markov kernel (SMK) and cyber attacks is …

This work investigates the asynchronous fault detection filtering issue for discrete-time
piecewise homogeneous Markov jump systems. By resorting to a dual hidden Markov …

This paper is concerned with the joint state and fault estimation problem for a class of
uncertain time-varying nonlinear stochastic systems with randomly occurring faults and …

This paper focuses on the state estimator design problem for a switched neural network
(SNN) with probabilistic quantized outputs, where the switching process is governed by a …

In this paper, the problem of generalized state estimation for an array of Markovian coupled
networks under the round-Robin protocol (RRP) and redundant channels is investigated by …