Analysis of cost function based on Kullback-Leibler divergence in independent component analysis for two uniformly distributed source signals

Kota Tanzawa, Shunsuke Koshita, Masahide Abe, Masayuki Kawamata

研究成果: Article査読

抄録

Independent component analysis plays a central role in blind source separation, leading to many applications of signal processing such as telecommunications, speech processing, and biomedical signal processing. Although the independent component analysis requires cost functions for evaluation of mutual independence of observed signals, little has been reported on theoretical investigation of the characteristics of such cost functions. In this paper, we mathematically analyze the cost function based on Kullback-Leibler divergence in independent component analysis. Our analysis proves that the cost function becomes unimodal when the number of source signals is two and both of the source signals have uniform distributions. In order to derive this result, we make use of whitening of observed signals and we describe the cost function in closed-form.

本文言語English
ページ(範囲)282-286
ページ数5
ジャーナルIEEJ Transactions on Electronics, Information and Systems
138
4
DOI
出版ステータスPublished - 2018 1 1

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

フィンガープリント 「Analysis of cost function based on Kullback-Leibler divergence in independent component analysis for two uniformly distributed source signals」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル