Approximate entropy (ApEn) was introduced to investigate the complexity and regularity in time-series data of different patterns of spontaneous neuron firing.
引入近似熵(ApEn)统计方法衡量神经元不同自发活动模式时间序列的复杂度和规律性。
参考来源 - 培养神经元网络自发电信号的特性分析This thesis presents a new approach to characterize the acoustic emission signals of the structure cracking in the process of loading based on the Approximate Entropy (ApEn), which is a statistical measure that quantifies the regularity of a time series.
本文提出了一种新的结构裂纹声发射信号特征提取方法——近似熵法,近似熵是一种最近新发展起来的度量序列复杂性的统计方法。
参考来源 - 导管架平台结构模型裂纹扩展声发射特征提取·2,447,543篇论文数据，部分数据来源于NoteExpress
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The perioperative EEG non-linear topographic map of approximate entropy was recorded.
记录围术期近似熵脑电非线性地形图。
Approximate entropy be applied to cryptographic technology, designing a testing method of a random sequence.
把近似熵用于密码技术中，设计一种实用的随机数检验方法。
In this paper, the conventional pseudo-random sequence linear complexity is discussed, and a new criterion is proposed, based on the approximate entropy.
分析了已有的序列线性复杂度分析方法，提出了用近似熵算法计算混沌运动的测度熵，作为衡量混沌伪随机序列复杂度的标准。
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