Renyi entropy measures of heart rate Gaussianity
Renyi entropy measures of heart rate Gaussianity
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DOI：
10.1109/tbme.2005.859782
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发表时间：
2006-01-01
影响因子：
4.6
通讯作者：
Lake, DE
中科院分区：
文献类型：
--
作者：
Lake, DE
样本熵和近似熵是已成功用于研究心率（HR）的确定性动力学的度量。一个互补的随机的观点和启发式的论点，使用中心极限定理表明，高斯的HR是一个互补的措施的生理复杂性的基础信号转导过程。伦维熵（Renvi entropy，或q-entropy）是一种在许多应用中广泛使用的高斯性度量。这个家族中特别重要的成员是微分（或香农）熵（q = 1）和二次熵（q = 2）。本文引入微分熵率和条件Renyi熵率的概念，并结合布尔格定理，给出了线性随机过程的高斯性测度。稳健的算法估计这些数量的沿着估计其标准误差。
Sample entropy and approximate entropy are measures that have been successfully utilized to study the deterministic dynamics of heart rate (HR). A complementary stochastic point of view and a heuristic argument using the Central Limit Theorem suggests that the Gaussianity of HR is a complementary measure of the physiological complexity of the underlying signal transduction processes. Renvi entropy (or q-entropy) is a widely used measure of Gaussianity in many applications. Particularly important members of this family are differential (or Shannon) entropy (q = 1) and quadratic entropy (q = 2). We introduce the concepts of differential and conditional Renyi entropy rate and, in conjunction with Burg's theorem, develop a measure of the Gaussianity of a linear random process. Robust algorithms for estimating these quantities are presented along with estimates of their standard errors.