On a Real-Time Blind Signal Separation Noise Reduction System

Ka Fai Cedric Yiu, Siow Yong Low

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Blind signal separation has been studied extensively in order to tackle the cocktail party problem. It explores spatial diversity of the received mixtures of sources by different sensors. By using the kurtosis measure, it is possible to select the source of interest out of a number of separated BSS outputs. Further noise cancellation can be achieved by adding an adaptive noise canceller (ANC) as postprocessing. However, the computation is rather intensive and an online implementation of the overall system is not straightforward. This paper intends to fill the gap by developing an FPGA hardware architecture to implement the system. Subband processing is explored and detailed functional operations are profiled carefully. The final proposed FPGA system is able to handle signals with sample rate over 20000 samples per second.

Original languageEnglish
Article number3721756
Pages (from-to)1-10
Number of pages10
JournalInternational Journal of Reconfigurable Computing
Volume2018
DOIs
Publication statusPublished - 4 Dec 2018

ASJC Scopus subject areas

  • Hardware and Architecture

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