Robust adaptive local polynomial Fourier transform

A robust form of the local polynomial Fourier transform (LPFT) is introduced. This transform can produce a highly concentrated time-frequency (TF) representation for signals embedded in an impulse noise. Calculation of the adaptive parameter in the proposed transform is based on the concentration me...

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Bibliographic Details
Published inIEEE signal processing letters Vol. 11; no. 2; pp. 201 - 204
Main Author Djurovic, I.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2004
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptive signal processing
Chirp
Fourier transforms
Gaussian noise
Impulses
Mathematical analysis
Noise
Noise robustness
Polynomials
Representations
Signal analysis
Signal processing
Signal resolution
Sorting
Transforms
Working environment noise
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Summary:A robust form of the local polynomial Fourier transform (LPFT) is introduced. This transform can produce a highly concentrated time-frequency (TF) representation for signals embedded in an impulse noise. Calculation of the adaptive parameter in the proposed transform is based on the concentration measure. A modified form, calculated as a weighted sum of the robust LPFT, is proposed for multicomponent signals.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2003.821695