Publication Type:

Journal Article


The European Physical Journal Special Topics, Springer Berlin Heidelberg, Volume 222, Number 3-4, p.847–860 (2013)


Complexity measures are used in a number of applications including extraction of information from data such as ecological time series, detection of non-random structure in biomedical signals, testing of random number generators, language recognition and authorship attribution etc. Different complexity measures proposed in the literature like Shannon entropy, Relative entropy, Lempel-Ziv, Kolmogrov and Algorithmic complexity are mostly ineffective in analyzing short sequences that are further corrupted with noise.


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Cite this Research Publication

N. Nagaraj, Balasubramanian, K., and Dey, S., “A New Complexity Measure for Time Series Analysis and Classification”, The European Physical Journal Special Topics, vol. 222, pp. 847–860, 2013.