Blind source separation using the second derivative of the second characteristic function

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Abstract

A new algorithm for blind source separation is presented, which does not require any iterations with the raw data, and is therefore of a "closed-form" type. The algorithm is based on estimating the second-derivative matrices of the second joint characteristic function of the observations. These derivatives can be consistently estimated at various points, termed "processing points". A consistent estimate of the mixing matrix can in turn be obtained by applying approximate joint diagonalization to the estimated derivative matrices. Performance depends strongly on the choice of processing points, and can compare favorably to other BSS algorithms. We demonstrate the superior performance using simulations results.

Original languageEnglish
Title of host publicationCommunicationsSensor Array and Multichannel Signal Processing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3136-3139
Number of pages4
ISBN (Electronic)0780362934
DOIs
StatePublished - 2000
Event25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 - Istanbul, Turkey
Duration: 5 Jun 20009 Jun 2000

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume5
ISSN (Print)1520-6149

Conference

Conference25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000
Country/TerritoryTurkey
CityIstanbul
Period5/06/009/06/00

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