NDLI: Distributed data fusion using support vector machines

Content Provider	IEEE Xplore Digital Library
Author	Challa, S. Palaniswami, M. Shilton, A.
Copyright Year	2002
Description	Author affiliation: Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia (Challa, S.)
Abstract	The basic quantity to be estimated in the Bayesian approach to data fusion is the conditional probability density function (CPDF). Computationally efficient particle filtering approaches are becoming more important in estimating these CPDFs. In this approach, IID samples are used to represent the conditional probability densities. However, their application in data fusion is severely limited due to the fact that the information is stored in the form of a large set of samples. In all practical data fusion systems that have limited communication bandwidth, broadcasting this probabilistic information, available as a set of samples, to the fusion center is impractical. Support vector machines, through statistical learning theory, provide a way of compressing information by generating optimal kernal based representations. In this paper we use SVM to compress the probabilistic information available in the form of IID samples and apply it to solve the Bayesian data fusion problem. We demonstrate this technique on a multi-sensor tracking example.
Starting Page	881
Ending Page	885
File Size	298957
Page Count	5
File Format	PDF
ISBN	0972184414
DOI	10.1109/ICIF.2002.1020902
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-07-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Int. Soc. of Information Fusion
Subject Keyword	Support vector machines Bayesian methods Remote sensing Density functional theory Filtering Statistical learning Bandwidth Fusion power generation Particle filters Recursive estimation
Content Type	Text
Resource Type	Article

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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
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