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Time-frequency representation of digital signals and systems based on short-time Fourier analysis

Portnoff, M.·1980·IEEE Transactions on Acoustics, Speech, and Signal Processing

Abstract

This paper develops a representation for discrete-time signals and systems based on short-time Fourier analysis. The short-time Fourier transform and the time-varying frequency response are reviewed as representations for signals and linear time-varying systems. The problems of representing a signal by its short-time Fourier transform and synthesizing a signal from its transform are considered. A new synthesis equation is introduced that is sufficiently general to describe apparently different synthesis methods reported in the literature. It is shown that a class of linear-filtering problems can be represented as the product of the time-varying frequency response of the filter multiplied by the short-time Fourier transform of the input signal. The representation of a signal by samples of its short-time Fourier transform is applied to the linear filtering problem. This representation is of practical significance because there exists a computationally efficient algorithm for implementing such systems. Finally, the methods of fast convolution age considered as special cases of this representation.

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Metadata

Authors
Portnoff, M.
Venue
IEEE Transactions on Acoustics, Speech, and Signal Processing
Published
1980-02
Volume
28
Issue
1
Pages
55-69
ISSN
0096-3518 (ISSN-L)
OpenAlex
W1973119332
Cited by
656
References
0
FWCI
8.87
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Time-frequency representation of digital signals and systems based on short-time Fourier analysis. https://app.cochat.ai/papers/10.1109/tassp.1980.1163359
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Portnoff, M. (1980). Time-frequency representation of digital signals and systems based on short-time Fourier analysis. IEEE Transactions on Acoustics, Speech, and Signal Processing. https://doi.org/10.1109/tassp.1980.1163359

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.