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• W2141022431 abstract "Several methods have been proposed so far for the analysis of the integral pulse frequency modulation (IPFM) model and detecting its corresponding physiological information. Most of these methods rely on the low-pass filtering method to extract the modulating signal of the model. In this paper, the authors present an entirely new approach based on vector space theory. The new method is developed for a more comprehensive form of the IPFM model, namely the time-varying threshold integral pulse frequency modulation (TVTIPFM) model. The new method decomposes the driving signals of the TVTIPFM model into a series of orthogonal basis functions and constructs a matrix identity through which the input signals can be obtained by a parametric solution. As a particular case, the authors apply this method to R-R intervals of the SA node to discriminate between its autonomic nervous modulation and the stretch induced effect." @default.
• W2141022431 created "2016-06-24" @default.
• W2141022431 creator A5078168965 @default.
• W2141022431 creator A5082526083 @default.
• W2141022431 date "2001-01-01" @default.
• W2141022431 modified "2023-09-25" @default.
• W2141022431 title "Time-varying threshold integral pulse frequency modulation" @default.
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• W2141022431 doi "https://doi.org/10.1109/10.942584" @default.
• W2141022431 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/11534843" @default.
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