Adaptive noise cancellation using fast optimum block algorithms

Michael E. Deisher, Andreas Spanias

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

4 Scopus citations

Abstract

The application of block frequency domain (FFT-based) adaptive algorithms to noise cancellation is considered. Two classes of FFT-based algorithms are examined, namely, those associated with periodic convolution and those associated with linear convolution. In both cases normalized optimum convergence factors are considered. Experimental noise cancellation results are given using speech corrupted by white, colored, and harmonically structured noise (simulated engine noise). Quantitative and subjective evaluations are given for all the results, and trade-offs of performance versus computational complexity are established.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE International Symposium on Circuits and Systems
PublisherPubl by IEEE
Pages698-701
Number of pages4
Volume1
StatePublished - 1991
Event1991 IEEE International Symposium on Circuits and Systems Part 1 (of 5) - Singapore, Singapore
Duration: Jun 11 1991Jun 14 1991

Other

Other1991 IEEE International Symposium on Circuits and Systems Part 1 (of 5)
CitySingapore, Singapore
Period6/11/916/14/91

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

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