open access

https://hdl.handle.net/2115/39701

Divergence, Signal Decomposition and Information Geometry

英語

2009-10-04

Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference, International Organizing Committee

Proceedings : APSIPA ASC 2009 : Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference

APSIPA ASC 2009: Asia-Pacific Signal and Information Processing Association, 2009 Annual Summit and Conference. 4-7 October 2009. Sapporo, Japan. Plenary Session 2, Keynote Speech #2 (6 October 2009)

Divergence measures between two probability distributions or more generally two signals play a fundamental role in designing algorithms of signal processing and adaptation. We first elucidate geometrical and invariant structures of divergence measures such as Kullback-Leibler and Bregman divergences. They are useful for designing algorithms in vision analysis, signal processing and optimization. Algorithms and frameworks of signal separation will be surveyed from the geometrical point of view.

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