Sampling theorems for fractional band-limited signals and time-limited signals

Jin Zhang; Hui Zhao; Qi Wen Ran

Sampling theorems for fractional band-limited signals and time-limited signals

Jin Zhang^*
, Hui Zhao
, Qi Wen Ran

^*Corresponding author for this work

School of Astronautics, Harbin Institute of Technology
Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

Abstract

By using the theorems of fractional Fourier transform (FRFT) and wavelet subspace decomposition, we study the sampling theorems and the sampling relations for fractional band-limited signals and time-limited signals, and obtain new sampling theorems and sampling relations for fractional band-limited signals and time-limited signals. This sampling method makes the sampling space twice times as usual and the sampling frequency half as usual, which brings convenience for the further application of the FRFT in the fields of signal processing and communication.

Original language	English
Pages (from-to)	117-119
Number of pages	3
Journal	Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology
Volume	39
Issue number	SUPPL. 1
State	Published - Jun 2007
Externally published	Yes

Keywords

Sampling theorem
Signal processing
The fractional fourier transform

Cite this

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title = "Sampling theorems for fractional band-limited signals and time-limited signals",

abstract = "By using the theorems of fractional Fourier transform (FRFT) and wavelet subspace decomposition, we study the sampling theorems and the sampling relations for fractional band-limited signals and time-limited signals, and obtain new sampling theorems and sampling relations for fractional band-limited signals and time-limited signals. This sampling method makes the sampling space twice times as usual and the sampling frequency half as usual, which brings convenience for the further application of the FRFT in the fields of signal processing and communication.",

keywords = "Sampling theorem, Signal processing, The fractional fourier transform",

author = "Jin Zhang and Hui Zhao and Ran, \{Qi Wen\}",

year = "2007",

month = jun,

language = "英语",

volume = "39",

pages = "117--119",

journal = "Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology",

issn = "0367-6234",

publisher = "Harbin Institute of Technology",

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TY - JOUR

T1 - Sampling theorems for fractional band-limited signals and time-limited signals

AU - Zhang, Jin

AU - Zhao, Hui

AU - Ran, Qi Wen

PY - 2007/6

Y1 - 2007/6

N2 - By using the theorems of fractional Fourier transform (FRFT) and wavelet subspace decomposition, we study the sampling theorems and the sampling relations for fractional band-limited signals and time-limited signals, and obtain new sampling theorems and sampling relations for fractional band-limited signals and time-limited signals. This sampling method makes the sampling space twice times as usual and the sampling frequency half as usual, which brings convenience for the further application of the FRFT in the fields of signal processing and communication.

AB - By using the theorems of fractional Fourier transform (FRFT) and wavelet subspace decomposition, we study the sampling theorems and the sampling relations for fractional band-limited signals and time-limited signals, and obtain new sampling theorems and sampling relations for fractional band-limited signals and time-limited signals. This sampling method makes the sampling space twice times as usual and the sampling frequency half as usual, which brings convenience for the further application of the FRFT in the fields of signal processing and communication.

KW - Sampling theorem

KW - Signal processing

KW - The fractional fourier transform

UR - https://www.scopus.com/pages/publications/36549055647

M3 - 文章

AN - SCOPUS:36549055647

SN - 0367-6234

VL - 39

SP - 117

EP - 119

JO - Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology

JF - Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology

IS - SUPPL. 1

ER -

Sampling theorems for fractional band-limited signals and time-limited signals

Abstract

Keywords

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