Covariance-Based Estimation for Clustered Sensor Networks Subject to Random Deception Attacks

In this paper, a cluster-based approach is used to address the distributed fusion estimation problem (filtering and fixed-point smoothing) for discrete-time stochastic signals in the presence of random deception attacks. At each sampling time, measured outputs of the signal are provided by a network...

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Vydáno v:	Sensors (Basel, Switzerland) Ročník 19; číslo 14; s. 3112
Hlavní autoři:	Caballero-Águila, Raquel, Hermoso-Carazo, Aurora, Linares-Pérez, Josefa
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland MDPI AG 14.07.2019 MDPI
Témata:	Algorithms Big Data cluster-based approach Clustering Deception Design False information least-squares filtering least-squares fixed-point smoothing networked systems Sensors stochastic deception attacks Wireless networks Spain least-squares filtering least-squares fixed-point smoothing cluster-based approach networked systems stochastic deception attacks
ISSN:	1424-8220, 1424-8220
On-line přístup:	Získat plný text
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