Joint blind source separation and declipping: a geometric approach for time disjoint sources

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

Joint blind source separation and declipping : a geometric approach for time disjoint sources. / Turl, Alastair; Kaban, Ata.

2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) (2017). Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 220-225.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Turl, A & Kaban, A 2018, Joint blind source separation and declipping: a geometric approach for time disjoint sources. in 2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) (2017). Institute of Electrical and Electronics Engineers (IEEE), pp. 220-225, 17th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017, Bilbao, Spain, 18/12/17. https://doi.org/10.1109/ISSPIT.2017.8388645

APA

Turl, A., & Kaban, A. (2018). Joint blind source separation and declipping: a geometric approach for time disjoint sources. In 2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) (2017) (pp. 220-225). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ISSPIT.2017.8388645

Vancouver

Turl A, Kaban A. Joint blind source separation and declipping: a geometric approach for time disjoint sources. In 2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) (2017). Institute of Electrical and Electronics Engineers (IEEE). 2018. p. 220-225 https://doi.org/10.1109/ISSPIT.2017.8388645

Author

Turl, Alastair ; Kaban, Ata. / Joint blind source separation and declipping : a geometric approach for time disjoint sources. 2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) (2017). Institute of Electrical and Electronics Engineers (IEEE), 2018. pp. 220-225

Bibtex

@inproceedings{4f75b28ddaef481da1d02965cca8bcf3,
title = "Joint blind source separation and declipping: a geometric approach for time disjoint sources",
abstract = "Source separation remains a challenging problem, made even more challenging when the mixtures are distorted. We present a novel framework for the source separation from mixtures affected by clipping distortion. Our method combines ℓ1 minimization with knowledge about the geometry of clipped mixtures when the sources are disjoint in time. Our algorithm recovers the sources by solving a convex optimization problem, which is constrained by the clipping geometry. Comparative evaluation experiments show a significant increase in objective recovery performance of our proposed joint method compared to sequential approaches for speech and synthetic signals.",
keywords = "Optimization, Mathematical model, Estimation, Quantization (signal), Minimization, Information technology",
author = "Alastair Turl and Ata Kaban",
year = "2018",
month = jun,
day = "18",
doi = "10.1109/ISSPIT.2017.8388645",
language = "English",
isbn = "9781538646632",
pages = "220--225",
booktitle = "2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) (2017)",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
note = "17th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017 ; Conference date: 18-12-2017 Through 20-12-2017",

}

RIS

TY - GEN

T1 - Joint blind source separation and declipping

T2 - 17th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017

AU - Turl, Alastair

AU - Kaban, Ata

PY - 2018/6/18

Y1 - 2018/6/18

N2 - Source separation remains a challenging problem, made even more challenging when the mixtures are distorted. We present a novel framework for the source separation from mixtures affected by clipping distortion. Our method combines ℓ1 minimization with knowledge about the geometry of clipped mixtures when the sources are disjoint in time. Our algorithm recovers the sources by solving a convex optimization problem, which is constrained by the clipping geometry. Comparative evaluation experiments show a significant increase in objective recovery performance of our proposed joint method compared to sequential approaches for speech and synthetic signals.

AB - Source separation remains a challenging problem, made even more challenging when the mixtures are distorted. We present a novel framework for the source separation from mixtures affected by clipping distortion. Our method combines ℓ1 minimization with knowledge about the geometry of clipped mixtures when the sources are disjoint in time. Our algorithm recovers the sources by solving a convex optimization problem, which is constrained by the clipping geometry. Comparative evaluation experiments show a significant increase in objective recovery performance of our proposed joint method compared to sequential approaches for speech and synthetic signals.

KW - Optimization

KW - Mathematical model

KW - Estimation

KW - Quantization (signal)

KW - Minimization

KW - Information technology

UR - http://www.scopus.com/inward/record.url?scp=85050148572&partnerID=8YFLogxK

U2 - 10.1109/ISSPIT.2017.8388645

DO - 10.1109/ISSPIT.2017.8388645

M3 - Conference contribution

AN - SCOPUS:85050148572

SN - 9781538646632

SP - 220

EP - 225

BT - 2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) (2017)

PB - Institute of Electrical and Electronics Engineers (IEEE)

Y2 - 18 December 2017 through 20 December 2017

ER -