Novel fractional wavelet transform: Principles, MRA and application

被引:26
作者
Guo, Yong [1 ]
Li, Bing-Zhao [2 ]
Yang, Li-Dong [3 ]
机构
[1] Inner Mongolia Univ Sci & Technol, Sch Sci, Baotou 014010, Inner Mongolia, Peoples R China
[2] Beijing Inst Technol, Sch Math & Sci, Beijing 100081, Peoples R China
[3] Inner Mongolia Univ Sci & Technol, Sch Informat Engn, Baotou 014010, Inner Mongolia, Peoples R China
基金
中国国家自然科学基金;
关键词
Fractional wavelet transform; Wavelet transform; Fractional Fourier transform; Multiresolution analysis; Time-fractional-frequency analysis; TIME;
D O I
10.1016/j.dsp.2020.102937
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Wavelet transform (WT) can be viewed as a differently scaled bandpass filter in the frequency domain, so WT is not the optimal time-frequency representation method for those signals which are not band-limited in the frequency domain. A novel fractional wavelet transform (FRWT) is proposed to break the limitation of WT, it displays the time and fractional frequency information jointly in the time-fractional-frequency (TFF) plane. The definition and basic properties of FRWT are studied firstly. Furthermore, the multiresolution analysis and orthogonal fractional wavelets associated with FRWT are explored. Finally, the application of FRWT in the LFM signal TFF analysis is discussed and verified by simulations. The experimental results show that the energy concentration of LFM signal representation by proposed FRWT is better than that of some existing methods. The better energy concentration makes it can be further applied to the denoising, detection, parameter estimation and separation of LFM signal. (C) 2020 Elsevier Inc. All rights reserved.
引用
收藏
页数:15
相关论文
共 22 条
[1]   THE FRACTIONAL FOURIER-TRANSFORM AND TIME-FREQUENCY REPRESENTATIONS [J].
ALMEIDA, LB .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1994, 42 (11) :3084-3091
[2]   Logarithmic uncertainty principle, convolution theorem related to continuous fractional wavelet transform and its properties on a generalized Sobolev space [J].
Bahri, Mawardi ;
Ashino, Ryuichi .
INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING, 2017, 15 (05)
[3]   A new fractional wavelet transform [J].
Dai, Hongzhe ;
Zheng, Zhibao ;
Wang, Wei .
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2017, 44 :19-36
[4]   THE WAVELET TRANSFORM, TIME-FREQUENCY LOCALIZATION AND SIGNAL ANALYSIS [J].
DAUBECHIES, I .
IEEE TRANSACTIONS ON INFORMATION THEORY, 1990, 36 (05) :961-1005
[5]   Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool [J].
Daubechies, Ingrid ;
Lu, Jianfeng ;
Wu, Hau-Tieng .
APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS, 2011, 30 (02) :243-261
[6]   Research on resolution between multi-component LFM signals in the fractional Fourier domain [J].
Liu Feng ;
Xu HuiFa ;
Tao Ran ;
Wang Yue .
SCIENCE CHINA-INFORMATION SCIENCES, 2012, 55 (06) :1301-1312
[7]  
Mallat S, 2009, WAVELET TOUR OF SIGNAL PROCESSING: THE SPARSE WAY, P1
[8]   Fractional wavelet transform [J].
Mendlovic, D ;
Zalevsky, Z ;
Mas, D ;
Garcia, J ;
Ferreira, C .
APPLIED OPTICS, 1997, 36 (20) :4801-4806
[9]   Digital computation of the fractional Fourier transform [J].
Ozaktas, HM ;
Ankan, O ;
Kutay, MA ;
Bozdagi, G .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1996, 44 (09) :2141-2150
[10]   The generalized continuous wavelet transform associated with the fractional Fourier transform [J].
Prasad, Akhilesh ;
Manna, Santanu ;
Mahato, Ashutosh ;
Singh, V. K. .
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 2014, 259 :660-671