Rezek I A, Roberts S J
Department of Electrical and Electronic Engineering, Imperial College of Science, Technology, and Medicine, London, U.K.
IEEE Trans Biomed Eng. 1998 Sep;45(9):1186-91. doi: 10.1109/10.709563.
Traditional feature extraction methods describe signals in terms of amplitude and frequency. This paper takes a paradigm shift and investigates four stochastic-complexity features. Their advantages are demonstrated on synthetic and physiological signals; the latter recorded during periods of Cheyne-Stokes respiration, anesthesia, sleep, and motor-cortex investigation.
传统的特征提取方法根据幅度和频率来描述信号。本文进行了范式转变，研究了四种随机复杂性特征。它们的优势在合成信号和生理信号上得到了证明；后者是在潮式呼吸、麻醉、睡眠和运动皮层研究期间记录的。
