NDLI: Kernel-based deterministic blue-noise sampling of arbitrary probability density functions

Content Provider	IEEE Xplore Digital Library
Author	Hanebeck, U.D.
Copyright Year	2014
Description	Author affiliation: Intell. Sensor-Actuator-Syst. Lab. (ISAS), Karlsruhe Inst. of Technol. (KIT), Karlsruhe, Germany (Hanebeck, U.D.)
Abstract	This paper provides an efficient method for approximating a given continuous probability density function (pdf) by a Dirac mixture density. Optimal parameters are determined by systematically minimizing a distance measure. As standard distance measures are typically not well defined for discrete densities on continuous domains, we focus on shifting the mass distribution of the approximating density as close to the true density as possible. Instead of globally comparing the masses as in a previous paper, the key idea is to characterize individual Dirac components by kernel functions representing the spread of probability mass that is appropriate at a given location. A distance measure is then obtained by comparing the deviation between the true density and the induced kernel density. This new method for Dirac mixture approximation provides high-quality approximation results, can handle arbitrary pdfs, allows considering constraints for, e.g., maintaining certain moments, and is fast enough for online processing.
Sponsorship	IEEE Inf. Theory Soc.
Starting Page	1
Ending Page	6
File Size	1027129
Page Count	6
File Format	PDF
ISBN	9781479930012
DOI	10.1109/CISS.2014.6814080
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-03-19
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	moment problem Density measurement sampling Vectors statistical distance measure Approximation methods Dirac mixture approximation Optimization Standards progressive processing Probability density function homotopy continuation Kernel
Content Type	Text
Resource Type	Article

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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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