An adaptive optimal-kernel time-frequency representation

Douglas L. Jones, Richard G. Baraniuk

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

9 Scopus citations

Abstract

Signal-dependent time-frequency representations perform well for a much wider range of signals than any fixed-kernel distribution. However, current signal-dependent representations are generally block-oriented techniques unsuitable for on-line implementation. The time-frequency representation presented here, based on a signal-dependent radially Gaussian kernel that adapts over time, tracks signal component variations over time and supports on-line implementation for signals of arbitrary length. The method uses a short-time ambiguity function for kernel optimization and as an intermediate step in computing constant-time slices of the time-frequency representation. While somewhat more expensive than fixed-kernel representations, this technique often provides much better performance.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1993
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages109-112
Number of pages4
ISBN (Electronic)0780309464
DOIs
StatePublished - 1993
Event1993 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1993 - Minneapolis, United States
Duration: Apr 27 1993Apr 30 1993

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume4
ISSN (Print)1520-6149

Conference

Conference1993 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1993
Country/TerritoryUnited States
CityMinneapolis
Period4/27/934/30/93

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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