Modified Fermat transforms for reliable and efficient de-noising of speech signals

C. Radhakrishnan, W. K. Jenkins, Carnell Hunter, R. N. Nickel

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

Abstract

Recently the Modified Fermat Number Transform (MFNT) based on Right-angle circular convolution (RCC) was extended to form a quadratic MFNT (QMFNT) by introducing Left-angle circular convolution (LCC) and interpreting the result as a quadratic representation of the convolution output. A similar concept was then extended to create a Modified Discrete Fourier Transform (MDFT). Both the QMFNT and the MDFT enable efficient convolution (correlation) without zero padding, resulting in improved computational efficiency. This paper investigates the use of the QMFNT and MDFT to implement an efficient novel speech de-noising algorithm that has potential applications for speech enhancement and speech recognition.

Original languageEnglish (US)
Title of host publicationConference Record of the 44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010
Pages546-550
Number of pages5
DOIs
StatePublished - Dec 1 2010
Event44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010 - Pacific Grove, CA, United States
Duration: Nov 7 2010Nov 10 2010

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other44th Asilomar Conference on Signals, Systems and Computers, Asilomar 2010
CountryUnited States
CityPacific Grove, CA
Period11/7/1011/10/10

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Computer Networks and Communications

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