Design of extraction algorithms based on second order statistics exploiting beamforming techniques

B.B.A.J. Bloemendal, J. Laar, van de, P.C.W. Sommen

Research output: Contribution to journalArticleAcademicpeer-review

3 Downloads (Pure)

Abstract

Signal extraction methods are becoming increasingly popular due to lower computational demands and less restrictive requirements than source separation algorithms. Many existing signal extraction algorithms extract interesting signals based on some known features of the sources. However, immediate extraction of the desired signal is not guaranteed, leading to inefficient and ad hoc deflation techniques. We present a design strategy for efficient signal extraction algorithms. First, by incorporating some amount of prior information in the form of a guess of either the autocorrelation function or the mixing column of the desired source, immediate identification of the desired extraction filter is guaranteed. Second, for a parameterized mixing system new techniques for the design and evaluation of signal extraction algorithms have been developed. These techniques are used to ensure immediate extraction of the desired signal by exploiting knowledge on physical parameters. The design procedure is flexible in the use of a priori information and leads to extraction algorithms that are robust to noise, deal with incomplete prior information, and handle modeling errors. Furthermore, the extraction algorithms can be used to identify extraction filters with different objectives. The design procedure and the properties of the extraction algorithms are evaluated by examples and experiments.
Original languageEnglish
Pages (from-to)125-137
Number of pages13
JournalSignal Processing
Volume96
Issue number2014
DOIs
Publication statusPublished - 2014

Fingerprint

Beamforming
Statistics
Source separation
Autocorrelation

Cite this

Bloemendal, B.B.A.J. ; Laar, van de, J. ; Sommen, P.C.W. / Design of extraction algorithms based on second order statistics exploiting beamforming techniques. In: Signal Processing. 2014 ; Vol. 96, No. 2014. pp. 125-137.
@article{788bd3fe9c3a4ab99ebdf26aa6760d68,
title = "Design of extraction algorithms based on second order statistics exploiting beamforming techniques",
abstract = "Signal extraction methods are becoming increasingly popular due to lower computational demands and less restrictive requirements than source separation algorithms. Many existing signal extraction algorithms extract interesting signals based on some known features of the sources. However, immediate extraction of the desired signal is not guaranteed, leading to inefficient and ad hoc deflation techniques. We present a design strategy for efficient signal extraction algorithms. First, by incorporating some amount of prior information in the form of a guess of either the autocorrelation function or the mixing column of the desired source, immediate identification of the desired extraction filter is guaranteed. Second, for a parameterized mixing system new techniques for the design and evaluation of signal extraction algorithms have been developed. These techniques are used to ensure immediate extraction of the desired signal by exploiting knowledge on physical parameters. The design procedure is flexible in the use of a priori information and leads to extraction algorithms that are robust to noise, deal with incomplete prior information, and handle modeling errors. Furthermore, the extraction algorithms can be used to identify extraction filters with different objectives. The design procedure and the properties of the extraction algorithms are evaluated by examples and experiments.",
author = "B.B.A.J. Bloemendal and {Laar, van de}, J. and P.C.W. Sommen",
year = "2014",
doi = "10.1016/j.sigpro.2013.09.019",
language = "English",
volume = "96",
pages = "125--137",
journal = "Signal Processing",
issn = "0165-1684",
publisher = "Elsevier",
number = "2014",

}

Design of extraction algorithms based on second order statistics exploiting beamforming techniques. / Bloemendal, B.B.A.J.; Laar, van de, J.; Sommen, P.C.W.

In: Signal Processing, Vol. 96, No. 2014, 2014, p. 125-137.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Design of extraction algorithms based on second order statistics exploiting beamforming techniques

AU - Bloemendal, B.B.A.J.

AU - Laar, van de, J.

AU - Sommen, P.C.W.

PY - 2014

Y1 - 2014

N2 - Signal extraction methods are becoming increasingly popular due to lower computational demands and less restrictive requirements than source separation algorithms. Many existing signal extraction algorithms extract interesting signals based on some known features of the sources. However, immediate extraction of the desired signal is not guaranteed, leading to inefficient and ad hoc deflation techniques. We present a design strategy for efficient signal extraction algorithms. First, by incorporating some amount of prior information in the form of a guess of either the autocorrelation function or the mixing column of the desired source, immediate identification of the desired extraction filter is guaranteed. Second, for a parameterized mixing system new techniques for the design and evaluation of signal extraction algorithms have been developed. These techniques are used to ensure immediate extraction of the desired signal by exploiting knowledge on physical parameters. The design procedure is flexible in the use of a priori information and leads to extraction algorithms that are robust to noise, deal with incomplete prior information, and handle modeling errors. Furthermore, the extraction algorithms can be used to identify extraction filters with different objectives. The design procedure and the properties of the extraction algorithms are evaluated by examples and experiments.

AB - Signal extraction methods are becoming increasingly popular due to lower computational demands and less restrictive requirements than source separation algorithms. Many existing signal extraction algorithms extract interesting signals based on some known features of the sources. However, immediate extraction of the desired signal is not guaranteed, leading to inefficient and ad hoc deflation techniques. We present a design strategy for efficient signal extraction algorithms. First, by incorporating some amount of prior information in the form of a guess of either the autocorrelation function or the mixing column of the desired source, immediate identification of the desired extraction filter is guaranteed. Second, for a parameterized mixing system new techniques for the design and evaluation of signal extraction algorithms have been developed. These techniques are used to ensure immediate extraction of the desired signal by exploiting knowledge on physical parameters. The design procedure is flexible in the use of a priori information and leads to extraction algorithms that are robust to noise, deal with incomplete prior information, and handle modeling errors. Furthermore, the extraction algorithms can be used to identify extraction filters with different objectives. The design procedure and the properties of the extraction algorithms are evaluated by examples and experiments.

U2 - 10.1016/j.sigpro.2013.09.019

DO - 10.1016/j.sigpro.2013.09.019

M3 - Article

VL - 96

SP - 125

EP - 137

JO - Signal Processing

JF - Signal Processing

SN - 0165-1684

IS - 2014

ER -