Adaptive short-time Fourier analysis

Richard N. Czerwinski, Douglas L. Jones

Research output: Contribution to journalArticle

Abstract

This letter presents a method of adaptively adjusting the window length used in short-time Fourier analysis, related to our earlier work in which we developed a means of adaptively optimizing the performance of the cone kernel distribution (CKD). The optimal CKD cone length is, by definition, a measure of the interval over which the signal has constant or slowly changing frequency structure. This letter shows that this length can also be used to compute a time-varying short-time Fourier transform (STFT). The resulting adaptive STFT shares many desirable properties with the adaptive CKD, such as the ability to adapt to transient as well as long-term signal components. The optimization requires O( N) operations per step, less than the fast Fourier transform (FFT) used in computing each time slice, making it competitive in complexity with nonadaptive time-frequency algorithms.

Original languageEnglish (US)
Pages (from-to)42-45
Number of pages4
JournalIEEE Signal Processing Letters
Volume4
Issue number2
DOIs
StatePublished - Dec 1 1997

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Fourier analysis
Fourier Analysis
Cones
Cone
Short-time Fourier Transform
kernel
Fourier transforms
Fast Fourier transform
Slice
Fast Fourier transforms
Time-varying
Interval
Optimization
Computing

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

Cite this

Adaptive short-time Fourier analysis. / Czerwinski, Richard N.; Jones, Douglas L.

In: IEEE Signal Processing Letters, Vol. 4, No. 2, 01.12.1997, p. 42-45.

Research output: Contribution to journalArticle

Czerwinski, Richard N. ; Jones, Douglas L. / Adaptive short-time Fourier analysis. In: IEEE Signal Processing Letters. 1997 ; Vol. 4, No. 2. pp. 42-45.
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