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

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

Authors

Colleges, School and Institutes

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.

Details

Original languageEnglish
Title of host publication2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) (2017)
Publication statusPublished - 18 Jun 2018
Event17th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017 - Bilbao, Spain
Duration: 18 Dec 201720 Dec 2017

Conference

Conference17th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017
CountrySpain
CityBilbao
Period18/12/1720/12/17

Keywords

  • Optimization, Mathematical model, Estimation, Quantization (signal), Minimization, Information technology