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Gradient flow independent component analysis in micropower VLSI

  • Johns Hopkins University

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

14 Scopus citations

Abstract

We present micropower mixed-signal VLSI hardware for real-time blind separation and localization of acoustic sources. Gradient flow representation of the traveling wave signals acquired over a miniature (1cm diameter) array of four microphones yields linearly mixed instantaneous observations of the time-differentiated sources, separated and localized by independent component analysis (ICA). The gradient flow and ICA processors each measure 3mm × 3mm in 0.5 μm CMOS, and consume 54 μW and 180 μW power, respectively, from a 3 V supply at 16 ks/s sampling rate. Experiments demonstrate perceptually clear (12dB) separation and precise localization of two speech sources presented through speakers positioned at 1.5m from the array on a conference room table. Analysis of the multipath residuals shows that they are spectrally diffuse, and void of the direct path.

Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 18 - Proceedings of the 2005 Conference
Pages187-194
Number of pages8
StatePublished - 2005
Event2005 Annual Conference on Neural Information Processing Systems, NIPS 2005 - Vancouver, BC, Canada
Duration: Dec 5 2005Dec 8 2005

Publication series

NameAdvances in Neural Information Processing Systems
ISSN (Print)1049-5258

Conference

Conference2005 Annual Conference on Neural Information Processing Systems, NIPS 2005
Country/TerritoryCanada
CityVancouver, BC
Period12/5/0512/8/05

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