Common spatial pattern (CSP) technique has been very popular in terms of
electroencephalogram (EEG) features extraction in motor imagery (MI)-based brain …

Nowadays, neural networks have been widely applied in many fields such as pattern
recognition, signal and image processing and control theory. Over the past two decades or …

In this paper, we investigate the distributed recursive fault estimation problem for a class of
discrete time-varying systems with binary encoding schemes over a sensor network. The …

This article is concerned with the partial-node-based (PNB) state estimation problem for
delayed complex networks (DCNs) subject to intermittent measurement outliers (IMOs). In …

In this paper, the distributed fusion estimation problem is studied for a class of nonlinear
networked systems subject to unknown-but-bounded (UBB) noises. A bit rate constraint is …

This paper is concerned with the fusion filtering problem for time-varying singular systems
with random transmission delays (RTDs) and packet dropout (PD) compensations. Here, the …

Accurate photovoltaic power forecasting is crucial for power dispatch planning, maintenance
scheduling and regulation. In this paper, a hybrid photovoltaic power forecasting model is …

In this paper, a novel outlier-resistant filtering problem is concerned for a class of networked
systems with dead-zone-like censoring under the weighted try-once-discard protocol …

This article is concerned with the distributed state estimation problem over wireless sensor
networks (WSNs), where each smart sensor is capable of harvesting energy from the …

This paper deals with the distributed-consensus state estimation problem for a class of
discrete time-varying systems with integral measurements over sensor networks. The …