DocumentCode
624630
Title
A fast trend extraction for the analysis of temperature data
Author
Yang Da ; Wang Xiaotong ; Xu Guanlei ; Su Shipeng
Author_Institution
Navig. Dept., Dalian Navy Acad., Dalian, China
fYear
2013
fDate
9-11 June 2013
Firstpage
338
Lastpage
342
Abstract
Trend extraction is one of the major contents of time series analysis. This paper employs a novel trend extraction method based on multi-scale extrema of signals to analyze the trend of temperature data. This approach is model-free, adaptive, fast, flexible and free of sifting-process applied in empirical mode decomposition (EMD). The practical temperature data series is analyzed and the changing trend can be extracted as fast as possible. In addition, the comparison with other methods based EMD is also presented to show the advantages of the proposed method in application of trend extraction and analysis for temperature data.
Keywords
filtering theory; time series; EMD; empirical mode decomposition; multiscale extrema; nonparametric linear filtering approach; novel fast trend extraction method; singular spectrum analysis; temperature data; time series analysis; Binary trees; Data mining; Interpolation; Market research; Temperature distribution; Time series analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Information Processing (ICICIP), 2013 Fourth International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4673-6248-1
Type
conf
DOI
10.1109/ICICIP.2013.6568094
Filename
6568094
Link To Document