Kalman Filtering and Clustering in Sensor Networks

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Standard

Kalman Filtering and Clustering in Sensor Networks. / Talebi, Sayed Pouria; Werner, Stefan; Koivunen, Visa.

2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. Vuosikerta 2018-April United States : IEEE, 2018. s. 4309-4313 8462039 (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing).

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Harvard

Talebi, SP, Werner, S & Koivunen, V 2018, Kalman Filtering and Clustering in Sensor Networks. julkaisussa 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. Vuosikerta. 2018-April, 8462039, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, United States, Sivut 4309-4313, IEEE International Conference on Acoustics, Speech, and Signal Processing, Calgary, Kanada, 15/04/2018. https://doi.org/10.1109/ICASSP.2018.8462039

APA

Talebi, S. P., Werner, S., & Koivunen, V. (2018). Kalman Filtering and Clustering in Sensor Networks. teoksessa 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings (Vuosikerta 2018-April, Sivut 4309-4313). [8462039] (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing). United States: IEEE. https://doi.org/10.1109/ICASSP.2018.8462039

Vancouver

Talebi SP, Werner S, Koivunen V. Kalman Filtering and Clustering in Sensor Networks. julkaisussa 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. Vuosikerta 2018-April. United States: IEEE. 2018. s. 4309-4313. 8462039. (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing). https://doi.org/10.1109/ICASSP.2018.8462039

Author

Talebi, Sayed Pouria ; Werner, Stefan ; Koivunen, Visa. / Kalman Filtering and Clustering in Sensor Networks. 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings. Vuosikerta 2018-April United States : IEEE, 2018. Sivut 4309-4313 (Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing).

Bibtex - Lataa

@inproceedings{bfc8c13e8e6e46e7a54a9ff7458e7d3f,
title = "Kalman Filtering and Clustering in Sensor Networks",
abstract = "In this work, a distributed Kalman filtering and clustering framework for sensor networks tasked with tracking multiple state vector sequences is developed. This is achieved through recursively updating the likelihood of a state vector estimation from one agent offering valid information about the state vector of its neighbors, given the available observation data. These likelihoods then form the diffusion coefficients, used for information fusion over the sensor network. For rigour, the mean and mean square behavior of the developed Kalman filtering and clustering framework is analyzed, convergence criteria are established, and the performance of the developed framework is demonstrated in a simulation example.",
keywords = "Adaptive clustering, Adaptive learning over networks, Distributed Kalman filtering, Multi-task sensor networks",
author = "Talebi, {Sayed Pouria} and Stefan Werner and Visa Koivunen",
year = "2018",
month = "9",
day = "10",
doi = "10.1109/ICASSP.2018.8462039",
language = "English",
isbn = "978-1-5386-4659-5",
volume = "2018-April",
series = "Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing",
publisher = "IEEE",
pages = "4309--4313",
booktitle = "2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings",
address = "United States",

}

RIS - Lataa

TY - GEN

T1 - Kalman Filtering and Clustering in Sensor Networks

AU - Talebi, Sayed Pouria

AU - Werner, Stefan

AU - Koivunen, Visa

PY - 2018/9/10

Y1 - 2018/9/10

N2 - In this work, a distributed Kalman filtering and clustering framework for sensor networks tasked with tracking multiple state vector sequences is developed. This is achieved through recursively updating the likelihood of a state vector estimation from one agent offering valid information about the state vector of its neighbors, given the available observation data. These likelihoods then form the diffusion coefficients, used for information fusion over the sensor network. For rigour, the mean and mean square behavior of the developed Kalman filtering and clustering framework is analyzed, convergence criteria are established, and the performance of the developed framework is demonstrated in a simulation example.

AB - In this work, a distributed Kalman filtering and clustering framework for sensor networks tasked with tracking multiple state vector sequences is developed. This is achieved through recursively updating the likelihood of a state vector estimation from one agent offering valid information about the state vector of its neighbors, given the available observation data. These likelihoods then form the diffusion coefficients, used for information fusion over the sensor network. For rigour, the mean and mean square behavior of the developed Kalman filtering and clustering framework is analyzed, convergence criteria are established, and the performance of the developed framework is demonstrated in a simulation example.

KW - Adaptive clustering

KW - Adaptive learning over networks

KW - Distributed Kalman filtering

KW - Multi-task sensor networks

UR - http://www.scopus.com/inward/record.url?scp=85054269775&partnerID=8YFLogxK

U2 - 10.1109/ICASSP.2018.8462039

DO - 10.1109/ICASSP.2018.8462039

M3 - Conference contribution

AN - SCOPUS:85054269775

SN - 978-1-5386-4659-5

VL - 2018-April

T3 - Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing

SP - 4309

EP - 4313

BT - 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings

PB - IEEE

CY - United States

ER -

ID: 28749085