A FAST ALGORITHM FOR COMPUTING SAMPLE ENTROPY
2011 ◽
Vol 03
(01n02)
◽
pp. 167-186
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Keyword(s):
Sample entropy is a widely used tool for quantifying complexity of a biological system. Computing sample entropy directly using its definition requires large computational costs. We propose a fast algorithm based on a k-d tree data structure for computing sample entropy. We prove that the time complexity of the proposed algorithm is [Formula: see text] and its space complexity is O(N log N), where N is the length of the input time series and m is the length of its pattern templates. We present a numerical experiment that demonstrates significant improvement of the proposed algorithm in computing time.
2014 ◽
Vol 10
(1)
◽
pp. 42-56
◽
2007 ◽
pp. 764-785
2007 ◽
pp. 574-603
2020 ◽
Vol 129
◽
pp. 232-239
◽
2017 ◽
Vol 13
(4)
◽
pp. 1556-1565
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Keyword(s):
2010 ◽
Vol 36
(5)
◽
pp. 818-834
◽