Event-triggered distributed Bayes filter Article Swipe
Giorgio Battistelli
,
Luigi Chisci
,
Lin Gao
,
Daniela Selvi
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.23919/ecc.2019.8795966
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.23919/ecc.2019.8795966
The aim of this paper is to devise a strategy that is able to reduce communication bandwidth and, consequently, energy consumption in the context of distributed state estimation over a peer-to-peer sensor network. Specifically, a distributed Bayes filter with event-triggered communication is developed by enforcing each node to transmit its local information to the neighbors only when the Kullback-Leibler divergence between the current local posterior and the one predictable from the last transmission exceeds a preset threshold. The stability of the proposed eventtriggered distributed Bayes filter is proved in the linear-Gaussian (Kalman filter) case. The performance of the proposed algorithm is also evaluated through simulation experiments concerning a target tracking application.
Related Topics
Concepts
Computer science
Kalman filter
Bayes' theorem
Bandwidth (computing)
Context (archaeology)
Filter (signal processing)
Real-time computing
Node (physics)
Transmission (telecommunications)
Event (particle physics)
Algorithm
Control theory (sociology)
Bayesian probability
Computer network
Artificial intelligence
Telecommunications
Engineering
Computer vision
Physics
Biology
Paleontology
Structural engineering
Control (management)
Quantum mechanics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.23919/ecc.2019.8795966
- OA Status
- green
- References
- 24
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W2917974268
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2917974268Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.23919/ecc.2019.8795966Digital Object Identifier
- Title
-
Event-triggered distributed Bayes filterWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-06-01Full publication date if available
- Authors
-
Giorgio Battistelli, Luigi Chisci, Lin Gao, Daniela SelviList of authors in order
- Landing page
-
https://doi.org/10.23919/ecc.2019.8795966Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/1902.09825Direct OA link when available
- Concepts
-
Computer science, Kalman filter, Bayes' theorem, Bandwidth (computing), Context (archaeology), Filter (signal processing), Real-time computing, Node (physics), Transmission (telecommunications), Event (particle physics), Algorithm, Control theory (sociology), Bayesian probability, Computer network, Artificial intelligence, Telecommunications, Engineering, Computer vision, Physics, Biology, Paleontology, Structural engineering, Control (management), Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
24Number of works referenced by this work
- Related works (count)
-
20Other works algorithmically related by OpenAlex
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