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Models of Markov Chain with Weights and Its Application in Predicting the Magnetic Field Intensity of Magnetocardiogram Signal

机译:马尔可夫链与重量的模型及其在预测磁铁电压仪信号磁场强度的应用

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摘要

Magnetocardiogram (MCG) signal is a kind of non-stationary signal reflecting the changes of cardiac magnetic field. It has practical significance to study the MCG signal and predict its change trend, which can help to analyze cardiac electrophysiological activities. In this article, Markov verification is carried out on MCG signals, it was possible to predict the magnetic field intensity of the MCG signal by Markov chain. Combined with the initial data acquired by the SQUID, it was feasible to predict the magnetic field intensity of the MCG signal by models of Markov chain with weights.
机译:磁进仪(MCG)信号是一种非静止信号,反映了心脏磁场的变化。研究MCG信号并预测其改变趋势具有现实意义,可以帮助分析心脏电生理活动。在本文中,马尔可夫验证在MCG信号上进行,可以通过马尔可夫链预测MCG信号的磁场强度。结合鱿鱼获取的初始数据,可以通过具有重量的马尔可夫链的模型来预测MCG信号的磁场强度是可行的。

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