Uncertainty principles for the short-time linear canonical transform of complex signals
| Autor: | Bing-Zhao Li, Wen-Biao Gao |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Signal Processing (eess.SP)
Correctness Uncertainty principle Applied Mathematics Gaussian 020206 networking & telecommunications 02 engineering and technology Covariance Standard deviation symbols.namesake Computational Theory and Mathematics Artificial Intelligence Signal Processing FOS: Electrical engineering electronic engineering information engineering 0202 electrical engineering electronic engineering information engineering symbols Chirp Spectrogram 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Electrical Engineering and Systems Science - Signal Processing Electrical and Electronic Engineering Statistics Probability and Uncertainty Algorithm Mathematics |
| Zdroj: | Digital Signal Processing. 111:102953 |
| ISSN: | 1051-2004 |
| Popis: | The short-time linear canonical transform (STLCT) can be identified as a generalization of the short-time Fourier transform (STFT). It is a novel time-frequency analysis tool. In this paper, we generalize some different uncertainty principles for the STLCT of complex signals. Firstly, one uncertainty principle for the STLCT of complex signals in time and frequency domains is derived. Secondly, the uncertainty principle for the STLCT of complex signals in two STLCT domains is obtained. Finally, the uncertainty principle for the two conditional standard deviations of the spectrogram associated with the STLCT is discussed. Comment: 10 pages |
| Databáze: | OpenAIRE |
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