Then the information entropy feature analysis method based on local-wave was proposed, which was used to describe signal’s complexity in the intrinsic mode space.
在此基础上,提出局域波域的信息熵特征分析方法,用于定量刻画信号在基本模式空间中分布的复杂度。
参考来源 - 基于信号局部特征提取的机械故障诊断方法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
The relaxation detecting of effective feature segmentation is studied before matching capability of Scene Matching Algorithm of fuzzy entropy similarity metric can be improved.
研究了有效特征区域的松弛检测方法，对基于模糊熵差的景象匹配算法进行相应后处理，提高了匹配性能。
Finally, a novel robust feature parameter, Adaptive Subband Power Spectral Entropy (ASPSE), is presented to successfully detect endpoints in different background noises.
发现了一种新颖的鲁棒特征参数-自适应子带谱熵(aspse)，它能成功地在不同的背景噪声下检测语音端点。
The feature functions were reckoned as the most important part of the maximum entropy model which could affact the last result of system.
在最大熵等统计机器学习模型当中，特征函数的选择可以说是对系统整体性能影响最大的部分。
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