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- W1489782545 abstract "Any natural or biological signal can be seen as a linear combination of meaningful and non-meaningful structures. According to the theory of multiresolution wavelet expansions, one can quantify the degree of information those structures using entropy and then select the most meaningful ones. Herein we propose to use adaptive time and frequency transform (ATFT) to measure wavelet entropy, where one line of approach to ATFT is to use a matching pursuit (MP) framework. The proposed method is tested on a set of heartbeat intervals whose population is composed of healthy and pathological subjects. Our results show that wavelet entropy measure based on MP decomposition can capture significant differences between the analyzed cardiac states that are intrinsically related to the structure of the signal." @default.
- W1489782545 created "2016-06-24" @default.
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- W1489782545 date "2010-01-01" @default.
- W1489782545 modified "2023-09-26" @default.
- W1489782545 title "Wavelet Entropy Measure Based on Matching Pursuit Decomposition and Its Analysis to Heartbeat Intervals" @default.
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- W1489782545 doi "https://doi.org/10.1007/978-3-642-17537-4_62" @default.
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