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Some features of time-frequency representations of multicomponent signals
Abstract
The Wigner-Ville Distribution (WVD) is now known to be a convenient tool for the time-frequency analysis of non-stationary signals, and especially monocomponent ones. However, in the case of multicomponent signals, its bilinear structure is also known to create cross-terms without any physical significance. Starting with the general formulation of time-frequency representations, which only depend on an arbitrary kernel function, we first characterize properties of such cross-terms and then propose appropriate smoothings of the WVD in order to reduce their influence. Such suitable and versatile approximations are compared on synthetic and natural signals and an extension to time-frequency filtering is proposed.
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“The STFT family provides cross-term free time-frequency representations.”
From Short-time fourier transform: two fundamental properties and an optimal implementation (2003) · cites this paper as [10]
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Metadata
- Authors
- Flandrin, P.
- Corresponding author
- Flandrin, P.
- ORCID
- Flandrin, P.
- Venue
- ICASSP '84. IEEE International Conference on Acoustics, Speech, and Signal Processing
- Published
- 2005-03-24
- Volume
- 9
- Pages
- 266-269
- ISSN
- 1520-6149 (ISSN-L)
- OpenAlex
- W1925346143
- Cited by
- 239
- References
- 6
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 5 · 2023: 6 · 2022: 5 · 2021: 3 · 2020: 2 · 2019: 3 · 2018: 3 · 2017: 1 · 2016: 2 · 2015: 4 · 2014: 3 · 2013: 2 · 2012: 2
- FWCI
- 26.53
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Acoustics Speech and Signal Processing (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Applied Mathematics › Mathematical Analysis and Transform Methods
- Physical Sciences › Computer Science › Signal Processing › Sparse and Compressive Sensing Techniques
- Physical Sciences › Computer Science › Signal Processing › Music and Audio Processing
- Keywords
- Wigner-Ville distribution, multicomponent signals, cross terms, time-frequency representation, kernel functions, time-frequency filtering, non-stationary signals
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