Outliers carry significant information to reflect an anomaly mechanism, so outlier detection
facilitates relevant data mining. In terms of outlier detection, the classical approaches from …

In this article, a new outlier-resistant recursive filtering problem (RF) is studied for a class of
multisensor multirate networked systems under the weighted try-once-discard (WTOD) …

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 …

Indoor localization is of pivotal significance for a wide variety of services in the context of the
Internet of Things (IoT). Both ranging-based and fingerprint-based localization techniques …

Climate stress poses a threat to the agricultural sector, which is vital for both the economy
and livelihoods in general. Quantifying its risk to food security, livelihoods, and sustainability …

Smart grid is a large complex network with a myriad of vulnerabilities, usually operated in
adversarial settings and regulated based on estimated system states. In this study, we …

State estimation is a fundamental task in many engineering fields, and therefore robust
nonlinear filtering techniques able to cope with misspecified, uncertain and/or corrupted …

In this article, a new outlier-resistant mechanism is proposed to deal with the variance-
constrained filtering problem for a class of networked systems subject to sensor resolution …

This paper proposes a variational Bayesian-based cubature Kalman filter to solve the state
estimation problem of nonlinear discrete-time systems under dynamic model mismatch and …

Uncertainties unavoidably exist in modeling for nonlinear systems: state equation,
measurement equation, and/or noises statistics might be uncertain. Such model mismatches …