NDLI: Sparse Bayesian consensus-based distributed field estimation

Content Provider	IEEE Xplore Digital Library
Author	Buchgraber, T. Shutin, D.
Copyright Year	2011
Description	Author affiliation: Signal Processing and Speech Comm. Lab., Graz University of Technology, Inffeldgasse 16c/EG, 8010, Austria (Buchgraber, T.) \|\| Department of Electrical Engineering, Princeton University, Equad-B311, Olden Street, NJ, 08544, USA (Shutin, D.)
Abstract	We present a fully decentralized algorithm that is inspired by sparse Bayesian learning (SBL) and can be used for non-parametric sparse estimation of unknown spatial functions - spatial fields - with wireless sensor networks (WSNs). It is assumed that a spatial field is represented as a linear combination of weighted fixed basis functions. By exploiting the similarity between the topology of a WSN and the proposed probabilistic graphical model for distributed SBL, a combination of variational inference and loopy belief propagation (LBP) is used to obtain the weights and the sparse subset of relevant basis functions. The algorithm requires only transmission between neighboring sensors and no multi-hop communication is needed. Furthermore, it does not rely on a fixed network structure and no information about the total number of sensors in the network is necessary. Due to consensus in the weight parameters between neighboring sensors, it is demonstrated that also the sparsity patterns of relevant basis functions generally agree. The effectiveness of the proposed algorithm is demonstrated with synthetic data.
Starting Page	1
Ending Page	8
File Size	325372
Page Count	8
File Format	PDF
ISBN	9781457711794
e-ISBN	9781457711800
e-ISBN	9781457711787
DOI	10.1109/ICSPCS.2011.6140888
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	consensus Wireless sensor networks message passing variational Distributed Probabilistic logic sparse Bayesian Vectors Inference algorithms Sensors Joints Convergence
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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