Symbolic transfer entropy-based premature signal analysis
Wang Jun(王俊)† and Yu Zheng-Feng(余正锋)
Image Processing and Image Communications Key Laboratory, School of Geography and Biological Information, Nanjing University of Posts & Telecommunications, Nanjing 210003, China
Abstract In this paper, we use symbolic transfer entropy to study the coupling strength between premature signals. Numerical experiments show that three types of signal couplings are in the same direction. Among them, normal signal coupling is the strongest, followed by that of premature ventricular contractions, and that of atrial premature beats is the weakest. The T test shows that the entropies of the three signals are distinct. Symbolic transfer entropy requires less data, can distinguish the three types of signals and has very good computational efficiency.
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