Recursive filtering for nonlinear systems, one of the core technologies of modern industrial
systems, is an ever-increasing research topic from the control and computer communities …

In this paper, the extended Kalman filtering problem is investigated for a class of nonlinear
systems with multiple missing measurements over a finite horizon. Both deterministic and …

This paper is concerned with the H∞ filtering problem for a class of networked systems
subject to randomly occurring distributed state delays, nonlinearities, sensor saturation as …

In this article, the recursive filtering problem is investigated for a class of time-varying
complex networks with state saturations and random coupling strengths under an event …

This paper focuses on the design problem of a recursive networked strong tracking filter
(NSTF) for a class of nonlinear networked systems with parameter perturbations and …

In many areas of human endeavour, the systems involved are not available for direct
measurement. Instead, by combining mathematical models for a system's evolution with …

This paper studies the extended Kalman filtering problem for a class of nonlinear discrete-
time systems with random transmission delays (RTDs) and RTD-induced packet disorders …

This article deals with the recursive filtering issue for a class of nonlinear complex networks
(CNs) with switching topologies, random sensor failures and dynamic event-triggered …

The Kalman Filter (KF) is one of the most widely used methods for tracking and estimation
due to its simplicity, optimality, tractability and robustness. However, the application of the KF …

The main goal of filtering is to obtain, recursively in time, good estimates of the state of a
stochastic dynamical system based on noisy partial observations of the same. In settings …