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首页> 外文会议>2011 IEEE International Conference on Information and Automation >A novel instantaneous phase difference estimator: piecewise maximum cross-correlation function
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A novel instantaneous phase difference estimator: piecewise maximum cross-correlation function

机译：一种新颖的瞬时相位差估计器：分段最大互相关函数

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摘要

The instantaneous phase synchrony estimation of biomedical signals is of increasing concern in terms of revealing bivariate dynamics of biological systems. The estimation of phase synchronization contains two major parts: the phase difference estimation and the synchronization index calculation. In recent studies of cerebral autoregulation (CA), a number of instantaneous phase difference estimation methods have been proposed to study instantaneous dynamic between arterial blood pressure (ABP) and cerebral blood flow velocity (CBFV). In this study, we took complex Morlet wavelet (CMW), the most widely used method as an example to discuss the possible limitations and propose a time-shift based method, piecewise maximum cross correlation function (PMCC) method. The analysis and the results show that PMCC avoids the trade-off between time and frequency resolution which exists in wavelet or short time Fourier transform based methods, and performs well in anti-noise. We finally discussed the limitation of PMCC.
机译：就揭示生物系统的双变量动态而言，生物医学信号的瞬时相位同步估计越来越受到关注。相位同步的估计包括两个主要部分：相位差估计和同步指数计算。在最近的脑自动调节（CA）研究中，已经提出了许多瞬时相差估计方法来研究动脉血压（ABP）和脑血流速度（CBFV）之间的瞬时动态。在这项研究中，我们以最广泛使用的复数Morlet小波（CMW）为例，讨论了可能的局限性，并提出了一种基于时移的方法，即分段最大互相关函数（PMCC）方法。分析和结果表明，PMCC避免了在基于小波或短时傅立叶变换的方法中存在的时间和频率分辨率之间的权衡，并且在抗噪声方面表现良好。我们最后讨论了PMCC的局限性。

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