Novel convolution and correlation theorems for the fractional Fourier transform

Abstract The fractional Fourier transform (FRFT) plays an important role in many fields of optics and signal processing. Many results in Fourier analysis have been extended to the FRFT, including the convolution and correlation theorems. However, the convolution and correlation theorems don’t have the elegance and simplicity comparable to that of the Fourier transform (FT). In this paper, we will propose a new convolution as well as correlation structure for FRFT which have similar time domain to frequency domain mapping results as the classical FT. First, we introduce a new convolution structure for the FRFT, which is expressed by a one dimensional integral and easy to implement in filter design. The conventional convolution theorem in FT domain is shown to be special cases of our achieved results. Then, we derive a convolution theorem for discrete time signal in discrete time FRFT (DTFRFT) domain. Last, based on the new convolution structure, we present a new kind of correlation operation for the FRFT that also generalizes very nicely the classical result for FT.

[1]  LJubisa Stankovic,et al.  Fractional Fourier transform as a signal processing tool: An overview of recent developments , 2011, Signal Process..

[2]  Ashutosh Kumar Singh,et al.  On Convolution and Product Theorems for FRFT , 2012, Wirel. Pers. Commun..

[3]  Nicola Laurenti,et al.  A unified framework for the fractional Fourier transform , 1998, IEEE Trans. Signal Process..

[4]  Meng Xiangyi,et al.  Fractional Fourier domain analysis of decimation and interpolation , 2007 .

[5]  L. B. Almeida Product and Convolution Theorems for the Fractional Fourier Transform , 1997, IEEE Signal Processing Letters.

[6]  A. Mustafi,et al.  A novel blind source separation technique using fractional Fourier transform for denoising medical images , 2013 .

[7]  Huiyan Hao,et al.  Multi component LFM signal detection and parameter estimation based on EEMD-FRFT , 2013 .

[8]  Kehar Singh,et al.  Image encryption using fractional Mellin transform, structured phase filters, and phase retrieval , 2014 .

[9]  Deyun Wei,et al.  Spectrum measurement in the fractional Fourier domain , 2014 .

[10]  Tomaso Erseghe,et al.  Unified fractional Fourier transform and sampling theorem , 1999, IEEE Trans. Signal Process..

[11]  Soo-Chang Pei,et al.  Relations between fractional operations and time-frequency distributions, and their applications , 2001, IEEE Trans. Signal Process..

[12]  Li-Ying Tan,et al.  A Convolution and Product Theorem for the Linear Canonical Transform , 2009, IEEE Signal Processing Letters.

[13]  Deyun Wei,et al.  Sampling reconstruction of N-dimensional bandlimited images after multilinear filtering in fractional Fourier domain , 2013 .

[14]  Rafael Torres,et al.  Fractional convolution, fractional correlation and their translation invariance properties , 2010, Signal Process..

[15]  Kamalesh Kumar Sharma,et al.  Papoulis-like generalized sampling expansions in fractional Fourier domains and their application to superresolution , 2007 .

[16]  Luís B. Almeida,et al.  The fractional Fourier transform and time-frequency representations , 1994, IEEE Trans. Signal Process..

[17]  Deyun Wei,et al.  Generalized Sampling Expansion for Bandlimited Signals Associated With the Fractional Fourier Transform , 2010, IEEE Signal Processing Letters.

[18]  Ran Tao,et al.  The Poisson sum formulae associated with the fractional Fourier transform , 2009, Signal Process..

[19]  Xuejun Sha,et al.  Generalized convolution theorem associated with fractional Fourier transform , 2014, Wirel. Commun. Mob. Comput..

[20]  Olcay Akay,et al.  Fractional convolution and correlation via operator methods and an application to detection of linear FM signals , 2001, IEEE Trans. Signal Process..

[21]  Navdeep Goel,et al.  Modified correlation theorem for the linear canonical transform with representation transformation in quantum mechanics , 2014, Signal Image Video Process..

[22]  Xiang-Gen Xia On bandlimited signals with fractional Fourier transform , 1996, IEEE Signal Process. Lett..

[23]  Z. Zalevsky,et al.  The Fractional Fourier Transform: with Applications in Optics and Signal Processing , 2001 .

[24]  Lin Yuan,et al.  Image encryption based on nonseparable fractional Fourier transform and chaotic map , 2015 .

[25]  A. Zayed A convolution and product theorem for the fractional Fourier transform , 1998, IEEE Signal Process. Lett..

[26]  Qiwen Ran,et al.  Sampling of fractional bandlimited signals associated with fractional Fourier transform , 2012 .

[27]  Sudarshan Shinde Two Channel Paraunitary Filter Banks Based on Linear Canonical Transform , 2011, IEEE Transactions on Signal Processing.

[28]  Levent Onural,et al.  Convolution, filtering, and multiplexing in fractional Fourier domains and their relation to chirp and wavelet transforms , 1994 .

[29]  Gozde Bozdagi Akar,et al.  Digital computation of the fractional Fourier transform , 1996, IEEE Trans. Signal Process..

[30]  Rafael Torres,et al.  Sampling Theorem for Fractional Bandlimited Signals: A Self-Contained Proof. Application to Digital Holography , 2006, IEEE Signal Processing Letters.

[31]  Naitong Zhang,et al.  Multichannel Sampling and Reconstruction of Bandlimited Signals in Fractional Fourier Domain , 2010, IEEE Signal Processing Letters.

[32]  D Mendlovic,et al.  Fractional correlator with real-time control of the space-invariance property. , 1997, Applied optics.

[33]  Soo-Chang Pei,et al.  Fractional Fourier series expansion for finite signals and dual extension to discrete-time fractional Fourier transform , 1999, IEEE Trans. Signal Process..