Zobrazeno 1 - 10
of 110
pro vyhledávání: '"Aurora Hermoso-Carazo"'
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 8, Pp 14550-14577 (2023)
This paper examines the distributed filtering and fixed-point smoothing problems for networked systems, considering random parameter matrices, time-correlated additive noises and random deception attacks. The proposed distributed estimation algorithm
Externí odkaz:
https://doaj.org/article/58ae9f897a2b459e8c66c93a0d8a5f4c
Publikováno v:
Mathematics, Vol 10, Iss 4, p 662 (2022)
This paper focuses on the distributed fusion estimation problem in which a signal transmitted over wireless sensor networks is subject to deception attacks and random delays. We assume that each sensor can suffer attacks that may corrupt and/or modif
Externí odkaz:
https://doaj.org/article/9034f7e53614493ca52540ed17d501b5
Publikováno v:
Mathematics, Vol 8, Iss 11, p 1948 (2020)
This paper investigates the distributed fusion estimation of a signal for a class of multi-sensor systems with random uncertainties both in the sensor outputs and during the transmission connections. The measured outputs are assumed to be affected by
Externí odkaz:
https://doaj.org/article/3bd35ecb6ef344deaab759f048501ef0
Publikováno v:
Sensors, Vol 20, Iss 22, p 6445 (2020)
In this paper, the distributed filtering problem is addressed for a class of discrete-time stochastic systems over a sensor network with a given topology, susceptible to suffering deception attacks, launched by potential adversaries, which can random
Externí odkaz:
https://doaj.org/article/cdc674c5bbb14db8b4226739476252ce
Publikováno v:
Sensors, Vol 19, Iss 14, p 3112 (2019)
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, measur
Externí odkaz:
https://doaj.org/article/a47e90f825694491984b47d609a8473a
Publikováno v:
Sensors, Vol 18, Iss 8, p 2697 (2018)
This paper is concerned with the least-squares linear centralized estimation problem in multi-sensor network systems from measured outputs with uncertainties modeled by random parameter matrices. These measurements are transmitted to a central proces
Externí odkaz:
https://doaj.org/article/fced9440e2ae4819b6997366902fb607
Publikováno v:
Mathematics, Vol 5, Iss 3, p 45 (2017)
In this paper, the information fusion estimation problem is investigated for a class of multisensor linear systems affected by different kinds of stochastic uncertainties, using both the distributed and the centralized fusion methodologies. It is ass
Externí odkaz:
https://doaj.org/article/e32e1f9ee94241219bee5d1f4155b9dc
Publikováno v:
Sensors, Vol 16, Iss 6, p 847 (2016)
This paper is concerned with the distributed and centralized fusion filtering problems in sensor networked systems with random one-step delays in transmissions. The delays are described by Bernoulli variables correlated at consecutive sampling times,
Externí odkaz:
https://doaj.org/article/b98bf7ef2aa04b14a340dc10c3fbf51c
Publikováno v:
Mathematics; Volume 10; Issue 4; Pages: 662
This paper focuses on the distributed fusion estimation problem in which a signal transmitted over wireless sensor networks is subject to deception attacks and random delays. We assume that each sensor can suffer attacks that may corrupt and/or modif
Publikováno v:
International Journal of Systems Science. 51:731-745
This paper addresses the linear least-squares estimation of a signal from measurements subject to stochastic sensor gain degradation and random delays during the transmission. These uncertainty phenomena, common in network systems, have traditionally