Theory and applications of short-time linear canonical transform
The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time...
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Gespeichert in:
| Autor*in: |
Wei, Deyun [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Modelling SARS-CoV-2 transmission in a UK university setting - Hill, Edward M. ELSEVIER, 2021, a review journal, Orlando, Fla |
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| Übergeordnetes Werk: |
volume:118 ; year:2021 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.dsp.2021.103239 |
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ELV055509819 |
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| 520 | |a The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). | ||
| 520 | |a The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). | ||
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10.1016/j.dsp.2021.103239 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001542.pica (DE-627)ELV055509819 (ELSEVIER)S1051-2004(21)00278-5 DE-627 ger DE-627 rakwb eng 610 VZ 44.75 bkl Wei, Deyun verfasserin aut Theory and applications of short-time linear canonical transform 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). Linear canonical transform Elsevier Chirp signals Elsevier Short-time linear canonical transform Elsevier Short-time Fourier transform Elsevier Hu, Huimin oth Enthalten in Academic Press Hill, Edward M. ELSEVIER Modelling SARS-CoV-2 transmission in a UK university setting 2021 a review journal Orlando, Fla (DE-627)ELV006540295 volume:118 year:2021 pages:0 https://doi.org/10.1016/j.dsp.2021.103239 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.75 Infektionskrankheiten parasitäre Krankheiten Medizin VZ AR 118 2021 0 |
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10.1016/j.dsp.2021.103239 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001542.pica (DE-627)ELV055509819 (ELSEVIER)S1051-2004(21)00278-5 DE-627 ger DE-627 rakwb eng 610 VZ 44.75 bkl Wei, Deyun verfasserin aut Theory and applications of short-time linear canonical transform 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). Linear canonical transform Elsevier Chirp signals Elsevier Short-time linear canonical transform Elsevier Short-time Fourier transform Elsevier Hu, Huimin oth Enthalten in Academic Press Hill, Edward M. ELSEVIER Modelling SARS-CoV-2 transmission in a UK university setting 2021 a review journal Orlando, Fla (DE-627)ELV006540295 volume:118 year:2021 pages:0 https://doi.org/10.1016/j.dsp.2021.103239 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.75 Infektionskrankheiten parasitäre Krankheiten Medizin VZ AR 118 2021 0 |
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10.1016/j.dsp.2021.103239 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001542.pica (DE-627)ELV055509819 (ELSEVIER)S1051-2004(21)00278-5 DE-627 ger DE-627 rakwb eng 610 VZ 44.75 bkl Wei, Deyun verfasserin aut Theory and applications of short-time linear canonical transform 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). Linear canonical transform Elsevier Chirp signals Elsevier Short-time linear canonical transform Elsevier Short-time Fourier transform Elsevier Hu, Huimin oth Enthalten in Academic Press Hill, Edward M. ELSEVIER Modelling SARS-CoV-2 transmission in a UK university setting 2021 a review journal Orlando, Fla (DE-627)ELV006540295 volume:118 year:2021 pages:0 https://doi.org/10.1016/j.dsp.2021.103239 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.75 Infektionskrankheiten parasitäre Krankheiten Medizin VZ AR 118 2021 0 |
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10.1016/j.dsp.2021.103239 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001542.pica (DE-627)ELV055509819 (ELSEVIER)S1051-2004(21)00278-5 DE-627 ger DE-627 rakwb eng 610 VZ 44.75 bkl Wei, Deyun verfasserin aut Theory and applications of short-time linear canonical transform 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). Linear canonical transform Elsevier Chirp signals Elsevier Short-time linear canonical transform Elsevier Short-time Fourier transform Elsevier Hu, Huimin oth Enthalten in Academic Press Hill, Edward M. ELSEVIER Modelling SARS-CoV-2 transmission in a UK university setting 2021 a review journal Orlando, Fla (DE-627)ELV006540295 volume:118 year:2021 pages:0 https://doi.org/10.1016/j.dsp.2021.103239 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.75 Infektionskrankheiten parasitäre Krankheiten Medizin VZ AR 118 2021 0 |
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10.1016/j.dsp.2021.103239 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001542.pica (DE-627)ELV055509819 (ELSEVIER)S1051-2004(21)00278-5 DE-627 ger DE-627 rakwb eng 610 VZ 44.75 bkl Wei, Deyun verfasserin aut Theory and applications of short-time linear canonical transform 2021transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). Linear canonical transform Elsevier Chirp signals Elsevier Short-time linear canonical transform Elsevier Short-time Fourier transform Elsevier Hu, Huimin oth Enthalten in Academic Press Hill, Edward M. ELSEVIER Modelling SARS-CoV-2 transmission in a UK university setting 2021 a review journal Orlando, Fla (DE-627)ELV006540295 volume:118 year:2021 pages:0 https://doi.org/10.1016/j.dsp.2021.103239 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.75 Infektionskrankheiten parasitäre Krankheiten Medizin VZ AR 118 2021 0 |
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Theory and applications of short-time linear canonical transform |
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Theory and applications of short-time linear canonical transform |
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Wei, Deyun |
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Modelling SARS-CoV-2 transmission in a UK university setting |
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10.1016/j.dsp.2021.103239 |
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theory and applications of short-time linear canonical transform |
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Theory and applications of short-time linear canonical transform |
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The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). |
| abstractGer |
The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). |
| abstract_unstemmed |
The linear canonical transform (LCT) is a powerful tool for signal processing and analyzing the non-stationary signals. However, it fails to process the signals whose linear canonical frequencies change over time due to the lack of time localization information. In this paper, we use the short-time linear canonical transform (STLCT) to solve this problem. First, its one-dimensional and two-dimensional inverse transformations are derived. Also, we derive some basic properties and the convolution theorem. Then, we also provide the time-canonical-frequency analysis of this transform. Finally, we give the discrete form and filter interpretation of STLCT. Moreover, we study practical applications of STLCT in time-frequency analysis of chirp signals. The simulation results show that the time-frequency resolution of STLCT is better than that of short-time Fourier transform (STFT), wavelet transform (WT) and generalized S transform (GST). |
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Theory and applications of short-time linear canonical transform |
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https://doi.org/10.1016/j.dsp.2021.103239 |
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