Abstract:
Trend extraction is an important tool for the analysis of data sequences. This paper presents a new methodology for trend extraction based on Hilbert-Huang transform. Sig...Show MoreMetadata
Abstract:
Trend extraction is an important tool for the analysis of data sequences. This paper presents a new methodology for trend extraction based on Hilbert-Huang transform. Signals are initially decomposed through use of EMD into a finite number of intrinsic mode functions (IMFs). The Hilbert marginal spectrum of each IMF is then calculated and a new criterion, termed the cross energy ratio of the Hilbert marginal spectrum of consecutive IMFs, is defined. Finally, through use of the new criterion, the underlying trend is obtained by adaptively selecting appropriate IMFs obtained by EMD. Results from experimental trials are included to demonstrate the benefits of the proposed method for extracting trends in data streams.
Published in: 2012 8th International Symposium on Communication Systems, Networks & Digital Signal Processing (CSNDSP)
Date of Conference: 18-20 July 2012
Date Added to IEEE Xplore: 17 September 2012
ISBN Information: