Kullback-Leibler和重整化熵在癫痫患者脑电图中的应用
Kullback-Leibler and Renormalized Entropy: Applications to EEGs of Epilepsy Patients
摘要：
最近，提出了重整熵作为相对熵的新度量（P. Saparin等人，Chaos，Solitons & Fractals 4，1907（1994）），并应用于几种生理时间序列，包括癫痫患者的EEG。本文证明了该测度是一个修正的Kullback-Leibler（K-L）相对熵，并给出了与标准K-L熵相似的数值结果.后者比重整熵更好地区分例如癫痫发作和背景EEG的频率内容。因此，我们认为重整化熵可能并不像它的支持者所声称的那样有用。顺便说一下，我们也对这些方法的实施提出了一些批评意见。
英文摘要：
Recently, renormalized entropy was proposed as a novel measure of relative entropy (P. Saparin et al., Chaos, Solitons & Fractals 4, 1907 (1994)) and applied to several physiological time sequences, including EEGs of patients with epilepsy. We show here that this measure is just a modified Kullback-Leibler (K-L) relative entropy, and it gives similar numerical results to the standard K-L entropy. The latter better distinguishes frequency contents of e.g. seizure and background EEGs than renormalized entropy. We thus propose that renormalized entropy might not be as useful as claimed by its proponents. In passing we also make some critical remarks about the implementation of these methods.
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