Abstract
An improved sample entropy (SE) algorithm named weighted sample entropy(WSE) is proposed in this paper to optimize the problems existing in SE based on weighting. The principle of WSE algorithm is given, and the performance of it for dynamical change detection is analyzed using synthetic signal. The results show that WSE can accurately capture amplitude information and amplify the detection results of dynamical changes compared with SE and PE in the case of high complexity, but it requires a higher computation cost than the others. From all the analyses in this paper, we find that WSE has a better performance for dynamical change detection compared with the other three algorithms in abnormal amplitude.
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