Estimating the number of sources using independent component analysis

Hiroshi Sawada; Ryo Mukai; Shoko Araki; Shoji Makino

doi:10.1250/ast.26.450

Estimating the number of sources using independent component analysis

Hiroshi Sawada, Ryo Mukai, Shoko Araki, Shoji Makino

Research output: Contribution to journal › Article › peer-review

15 Citations (Scopus)

Abstract

A new approach for estimating the number of sources that employs independent component analysis (ICA) is discussed. Estimating the number of sources provides information for signal processing applications such as blind source separation (BSS) in the frequency domain. The new method can identify a noise component that includes reverberations by calculating the correlation of the envelopes. The results show that the characteristics of the proposed approach compare with the conventional eigenvalue-based method.

Original language	English
Pages (from-to)	450-452
Number of pages	3
Journal	Acoustical Science and Technology
Volume	26
Issue number	5
DOIs	https://doi.org/10.1250/ast.26.450
Publication status	Published - 2005
Externally published	Yes

Keywords

Convolutive mixtures
Eigenvalue of correlation matrix
Independent component analysis

ASJC Scopus subject areas

Acoustics and Ultrasonics

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10.1250/ast.26.450

Cite this

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abstract = "A new approach for estimating the number of sources that employs independent component analysis (ICA) is discussed. Estimating the number of sources provides information for signal processing applications such as blind source separation (BSS) in the frequency domain. The new method can identify a noise component that includes reverberations by calculating the correlation of the envelopes. The results show that the characteristics of the proposed approach compare with the conventional eigenvalue-based method.",

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AU - Sawada, Hiroshi

AU - Mukai, Ryo

AU - Araki, Shoko

AU - Makino, Shoji

PY - 2005

Y1 - 2005

N2 - A new approach for estimating the number of sources that employs independent component analysis (ICA) is discussed. Estimating the number of sources provides information for signal processing applications such as blind source separation (BSS) in the frequency domain. The new method can identify a noise component that includes reverberations by calculating the correlation of the envelopes. The results show that the characteristics of the proposed approach compare with the conventional eigenvalue-based method.

AB - A new approach for estimating the number of sources that employs independent component analysis (ICA) is discussed. Estimating the number of sources provides information for signal processing applications such as blind source separation (BSS) in the frequency domain. The new method can identify a noise component that includes reverberations by calculating the correlation of the envelopes. The results show that the characteristics of the proposed approach compare with the conventional eigenvalue-based method.

KW - Convolutive mixtures

KW - Eigenvalue of correlation matrix

KW - Independent component analysis

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Estimating the number of sources using independent component analysis

Abstract

Keywords

ASJC Scopus subject areas

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