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» Fast approximate correlation for massive time-series data
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TMI
2010
175views more  TMI 2010»
13 years 15 days ago
Spatially Adaptive Mixture Modeling for Analysis of fMRI Time Series
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...
Thomas Vincent, Laurent Risser, Philippe Ciuciu
SIGMOD
2006
ACM
137views Database» more  SIGMOD 2006»
14 years 6 months ago
Optimal multi-scale patterns in time series streams
We introduce a method to discover optimal local patterns, which concisely describe the main trends in a time series. Our approach examines the time series at multiple time scales ...
Spiros Papadimitriou, Philip S. Yu
SDM
2009
SIAM
164views Data Mining» more  SDM 2009»
14 years 3 months ago
Exact Discovery of Time Series Motifs.
Time series motifs are pairs of individual time series, or subsequences of a longer time series, which are very similar to each other. As with their discrete analogues in computat...
Abdullah Mueen, Eamonn J. Keogh, M. Brandon Westov...
MOBIHOC
2008
ACM
14 years 5 months ago
Fast and quality-guaranteed data streaming in resource-constrained sensor networks
In many emerging applications, data streams are monitored in a network environment. Due to limited communication bandwidth and other resource constraints, a critical and practical...
Emad Soroush, Kui Wu, Jian Pei
ICPR
2008
IEEE
14 years 6 days ago
An online polygonal approximation of digital signals and curves with Dynamic Programming algorithm
A fast online algorithm was developed for polygonal approximation of signals and curves with a minimum number of line segments for a given constraint on the standard deviation of ...
Alexander Kolesnikov