NDLI: A method for segmentation of switching dynamic modes in time series

Content Provider	IEEE Xplore Digital Library
Author	Lei Feng Kihwan Ju Chon, K.H.
Copyright Year	1996
Abstract	A method to identify switching dynamics in time series, based on Annealed Competition of Experts algorithm (ACE), has been developed by Kohlmorgen et al. Incorrect selection of embedding dimension and time delay of the signal significantly affect the performance of the ACE method, however. In this paper, we utilize systematic approaches based on mutual information and false nearest neighbor to determine appropriate embedding dimension and time delay. Moreover, we obtained further improvements to the original ACE method by incorporating a deterministic annealing approach as well as phase space closeness measure. Using these improved implementations, we have enhanced the performance of the ACE algorithm in determining the location of the switching of dynamic modes in the time series. The application of the improved ACE method to heart rate data obtained from rats during control and administration of double autonomic blockade conditions indicate that the improved ACE algorithm is able to segment dynamic mode changes with pinpoint accuracy and that its performance is superior to the original ACE algorithm.
Page Count	7
File Size	298829
Starting Page	1058
Ending Page	1064
File Format	PDF
ISSN	10834419
Volume Number	35
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal processing algorithms Annealing Clustering algorithms Hidden Markov models Delay effects Mutual information Nearest neighbor searches Extraterrestrial measurements Phase measurement Heart rate rival penalized clustering algorithm Annealed competition of experts deterministic annealing dynamics expectation maximization false nearest neighbor heart rate variability mutual information radial basis function
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Information Systems Electrical and Electronic Engineering Human-Computer Interaction Computer Science Applications Software

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