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Combined use of correlation dimension and entropy as discriminating measures for time series analysis

✍ Scribed by K.P. Harikrishnan; R. Misra; G. Ambika


Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
367 KB
Volume
14
Category
Article
ISSN
1007-5704

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✦ Synopsis


We show that the combined use of correlation dimension ðD 2 Þ and correlation entropy ðK 2 Þ as discriminating measures can extract a more accurate information regarding the different types of noise present in a time series data. For this, we make use of an algorithmic approach for computing D 2 and K 2 proposed by us recently [Harikrishnan KP, Misra R,