Wavelet Transform Application for/in Non-Stationary Time-Series Analysis: A Review

doi:10.3390/app9071345

	Wavelet Transform Application for/in Non-Stationary Time-Series Analysis: A Review
	Rhif, Manel 1; Ben Abbes, Ali 1,2; Farah, Imed Riadh 1,3; Martinez, Beatriz 4; Sang, Yanfang 5
刊名	APPLIED SCIENCES-BASEL
	2019-04-01
卷号	9 期号:7 页码:22
关键词	wavelet transform non stationary time series time-frequency decomposition applied sciences
DOI	10.3390/app9071345
通讯作者	Rhif, Manel(manel.rhif@ensi-uma.tn) ; Sang, Yanfang(sangyf@igsnrr.ac.cn)
英文摘要	Non-stationary time series (TS) analysis has gained an explosive interest over the recent decades in different applied sciences. In fact, several decomposition methods were developed in order to extract various components (e.g., seasonal, trend and abrupt components) from the non-stationary TS, which allows for an improved interpretation of the temporal variability. The wavelet transform (WT) has been successfully applied over an extraordinary range of fields in order to decompose the non-stationary TS into time-frequency domain. For this reason, the WT method is briefly introduced and reviewed in this paper. In addition, this latter includes different research and applications of the WT to non-stationary TS in seven different applied sciences fields, namely the geo-sciences and geophysics, remote sensing in vegetation analysis, engineering, hydrology, finance, medicine, and other fields, such as ecology, renewable energy, chemistry and history. Finally, five challenges and future works, such as the selection of the type of wavelet, selection of the adequate mother wavelet, selection of the scale, the combination between wavelet transform and machine learning algorithm and the interpretation of the obtained components, are also discussed.
资助项目	National Key Research and Development Program[2017YFA0603702] ; National Natural Science Foundation of China[91647110] ; Youth Innovation Promotion Association CAS[2017074]
WOS关键词	EMPIRICAL MODE DECOMPOSITION ; INFORMATION ; EXTRACTION ; SPECTRUM ; RETURNS ; MARKETS ; NOISE ; ECG
WOS研究方向	Chemistry ; Materials Science ; Physics
语种	英语
出版者	MDPI
WOS记录号	WOS:000466547500080
资助机构	National Key Research and Development Program ; National Natural Science Foundation of China ; Youth Innovation Promotion Association CAS
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/59073]
专题	中国科学院地理科学与资源研究所
通讯作者	Rhif, Manel; Sang, Yanfang
作者单位	1.Ecole Natl Sci Informat, Lab RIADI, La Manouba 2010, Tunisia 2.Univ Sherbrooke, Ctr Applicat & Rech Teledetect CARTEL, Sherbrooke, PQ J1K 2R1, Canada 3.IMT Atlantique, Lab ITI Dept, F-29238 Brest, France 4.Univ Valencia, Dept Fis Terra & Termodinam, E-46100 Valencia, Spain 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Rhif, Manel,Ben Abbes, Ali,Farah, Imed Riadh,et al. Wavelet Transform Application for/in Non-Stationary Time-Series Analysis: A Review[J]. APPLIED SCIENCES-BASEL,2019,9(7):22.
APA	Rhif, Manel,Ben Abbes, Ali,Farah, Imed Riadh,Martinez, Beatriz,&Sang, Yanfang.(2019).Wavelet Transform Application for/in Non-Stationary Time-Series Analysis: A Review.APPLIED SCIENCES-BASEL,9(7),22.
MLA	Rhif, Manel,et al."Wavelet Transform Application for/in Non-Stationary Time-Series Analysis: A Review".APPLIED SCIENCES-BASEL 9.7(2019):22.