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Analysis of source separation algorithms in industrial acoustic environments

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper shows the results from the computation cost evaluation of three blind source separation algorithms. The algorithms tested were: FastICA, Adaptive Algorithm Based on Natural Gradient, and Adaptive EASI Based on Relative Gradient. The algorithms were chosen for their relative simplicity, and taking into account their hardware implementation feasibility, either on a FPGA or an ASIC, as part of a system for acoustic localization of mobile agents in industrial environments.

Original languageEnglish
Title of host publication2015 IEEE 6th Latin American Symposium on Circuits and Systems, LASCAS 2015 - Conference Proceedings
EditorsAlfredo Arnaud, Fernando Silveira, Lorena Garcia
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479983322
DOIs
StatePublished - 9 Sep 2015
Event6th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2015 - Montevideo, Uruguay
Duration: 24 Feb 201527 Feb 2015

Publication series

Name2015 IEEE 6th Latin American Symposium on Circuits and Systems, LASCAS 2015 - Conference Proceedings

Conference

Conference6th IEEE Latin American Symposium on Circuits and Systems, LASCAS 2015
Country/TerritoryUruguay
CityMontevideo
Period24/02/1527/02/15

Keywords

  • Adaptive Algorithm Based on Natural Gradient
  • Adaptive EASI Based on Relative Gradient
  • Blind Source Separation (BSS)
  • FPGA
  • FastICA
  • acoustic localization

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