Date of Original Version

7-2010

Type

Article

Journal Title

Journal of Experimental & Theoretical Artificial Intelligence

Volume

23

Issue

23

First Page

255

Last Page

270

Rights Management

This is the accepted version of the article which has been published in final form at http://dx.doi.org/10.1080/0952813X.2010.505800

Abstract or Description

We formalize the notion of important extrema of a time series, that is, its major minima and maxima; analyze basic mathematical properties of important extrema; and apply these results to the problem of time-series compression. First, we define numeric importance levels of extrema in a series, and present algorithms for identifying major extrema and computing their importances. Then, we give a procedure for fast lossy compression of a time series at a given rate, by extracting its most important minima and maxima, and discarding the other points

DOI

10.1080/0952813X.2010.505800

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Published In

Journal of Experimental & Theoretical Artificial Intelligence, 23, 23, 255-270.