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The wavelet transform, time-frequency localization and signal analysis

Ingrid Daubechies · IEEE Transactions on Information Theory · 1990

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Author / responsible party
Ingrid Daubechies
Publisher
IEEE Transactions on Information Theory
Year
1990
Language
English

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Two different procedures for effecting a frequency analysis of a time-dependent signal locally in time are studied. The first procedure is the short-time or windowed Fourier transform; the second is the wavelet transform, in which high-frequency components are studied with sharper time resolution than low-frequency components. The similarities and the differences between these two methods are discussed. For both schemes a detailed study is made of the reconstruction method and its stability as a function of the chosen time-frequency density. Finally, the notion of time-frequency localization is made precise, within this framework, by two localization theorems.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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APA 7

Daubechies, I. (1990). The wavelet transform, time-frequency localization and signal analysis. https://doi.org/10.1109/18.57199

MLA

Daubechies, Ingrid. "The wavelet transform, time-frequency localization and signal analysis." 1990. https://doi.org/10.1109/18.57199.

Chicago

Daubechies, Ingrid. 1990. "The wavelet transform, time-frequency localization and signal analysis.". https://doi.org/10.1109/18.57199.

Harvard

Daubechies, I. 1990, The wavelet transform, time-frequency localization and signal analysis, IEEE Transactions on Information Theory, available at: https://doi.org/10.1109/18.57199 [Accessed 8 Aug. 2026].

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Resource details

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Title
The wavelet transform, time-frequency localization and signal analysis
Author / contributors
Ingrid Daubechies
Publisher
IEEE Transactions on Information Theory
Publication year
1990
Language
English

Subjects

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Time–frequency analysis; Wavelet; Algorithm; SIGNAL (programming language); Fourier transform; Wavelet transform; Stability (learning theory); Signal processing; Computer science; Mathematics; Function (biology); Speech recognition
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