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International Conference on Mechanical Engineering and Technology (ICMET-London 2011)

Editor
Garry Lee
Garry Lee
Information Engineering Research Institute
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ISBN:
9780791859896
No. of Pages:
906
Publisher:
ASME Press
Publication date:
2011

Trend extraction is an important tool for the analysis of data sequences. This paper presents a new methodology for trend extraction based on Empirical Mode Decomposition (EMD) and nonuniform filter banks. Signals are initially decomposed, through use of EMD, into a finite number of intrinsic mode functions (IMFs). The underlying trend is then obtained by adaptively selecting appropriate IMFs obtained by EMD using nonuniform filter banks. Results from experimental trials are included to the proposed method and provide an excellent mechanism for extracting trends in (possibly non-stationary) data.

Abstract
Keywords
Introduction
Review of Empirical Mode Decomposition
Trend Extraction VIA EMd and Nonuniform Filter Banks
Experimental Results and Discussion
Conclusion
Acknowledgments
References
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