loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Shivakumar Jolad 1 ; Ahmed Roman 2 ; Mahesh C. Shastry 3 ; Mihir Gadgil 4 and Ayanendranath Basu 5

Affiliations: 1 Indian Institute of Technology Gandhinagar, India ; 2 Virginia Tech, United States ; 3 Indian Institute of Science Education and Research Bhopal, India ; 4 Oregon Health & Science University, United States ; 5 Indian Statistical Institute, India

ISBN: 978-989-758-173-1

Keyword(s): Divergence Measures, Bhattacharyya Distance, Error Probability, F-divergence, Pattern Recognition, Signal Detection, Signal Classification.

Related Ontology Subjects/Areas/Topics: Applications ; Bayesian Models ; Classification ; Gaussian Processes ; Object Recognition ; Pattern Recognition ; Software Engineering ; Theory and Methods

Abstract: We introduce a new one-parameter family of divergence measures, called bounded Bhattacharyya distance (BBD) measures, for quantifying the dissimilarity between probability distributions. These measures are bounded, symmetric and positive semi-definite and do not require absolute continuity. In the asymptotic limit, BBD measure approaches the squared Hellinger distance. A generalized BBD measure for multiple distributions is also introduced. We prove an extension of a theorem of Bradt and Karlin for BBD relating Bayes error probability and divergence ranking. We show that BBD belongs to the class of generalized Csiszar f-divergence and derive some properties such as curvature and relation to Fisher Information. For distributions with vector valued parameters, the curvature matrix is related to the Fisher-Rao metric. We derive certain inequalities between BBD and well known measures such as Hellinger and Jensen-Shannon divergence. We also derive bounds on the Bayesian error probability. We give an application of these measures to the problem of signal detection where we compare two monochromatic signals buried in white noise and differing in frequency and amplitude. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.214.184.124

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Jolad, S.; Roman, A.; Shastry, M.; Gadgil, M. and Basu, A. (2016). A New Family of Bounded Divergence Measures and Application to Signal Detection.In Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-173-1, pages 72-83. DOI: 10.5220/0005695200720083

@conference{icpram16,
author={Shivakumar Jolad. and Ahmed Roman. and Mahesh C. Shastry. and Mihir Gadgil. and Ayanendranath Basu.},
title={A New Family of Bounded Divergence Measures and Application to Signal Detection},
booktitle={Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2016},
pages={72-83},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005695200720083},
isbn={978-989-758-173-1},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - A New Family of Bounded Divergence Measures and Application to Signal Detection
SN - 978-989-758-173-1
AU - Jolad, S.
AU - Roman, A.
AU - Shastry, M.
AU - Gadgil, M.
AU - Basu, A.
PY - 2016
SP - 72
EP - 83
DO - 10.5220/0005695200720083

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.