A signal-dependent evolution kernel for cohen class time-frequency distributions

Sudarshan Rao Nelatury, P. S. Moharir

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Cohen class time-frequency distributions serve as alternatives to the traditional spectrogram and are known for their ability to provide simultaneous resolution in time and frequency. They employ a kernel along with the signal's Wigner distribution. Kernel design has witnessed significant attention. Very recently Costa and Boudreaux-Bartels have proposed a multiform tiltable exponential distribution kernel containing six parameters. This paper presents optimization of these parameters using evolution programs.

Original languageEnglish (US)
Article numberSP980313
Pages (from-to)158-165
Number of pages8
JournalDigital Signal Processing: A Review Journal
Volume8
Issue number3
Publication statusPublished - Jan 1 1998

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All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

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