介绍了一种时间序列复杂度参数（排列熵）的论文

许多CD到MP3应用程序或下载的专辑都输出不明确的mp3文件名。 MRE将文件名约定恢复到mp3文件，而没有第三方信息源，它使用的是文件名/相册文件夹本身！

求图像的信息熵MATLAB

编写磁盘使用率和熵限制器（DUEL）是为了解决科罗拉多矿业大学N​​T Server实验中的性能问题，用于清理Windows NT实验中的用户配置文件。

图像信息熵计算，可计算出图像加密后是否是理想的随机图像，用来判断图像加密算法的效果，是评价一个图像加密算法的重要手段。通过输入加密后的图像，可利用该程序直接计算出图像的信息熵。

可以计算图像信息熵的代码，很好用哦，可以下下来进行一些图像处理 可以计算图像信息熵的代码，很好用哦，可以下下来进行一些图像处理

通过求解EEG信号的模糊熵来表征信号的复杂度，输出结果对应脑电通道数的数据向量，可以结合脑电地形图的程序，画脑电信号地形图，直观看出脑电某些区域的复杂度

信息熵，一维信号，二维图像等，计算新的信息熵值，来判断信号是否具有规律性，MATLAB，故障诊断算法等均会用到

matlab自写最大熵程序，目前有一个问题，就是初值的确定。希望和大家交流，能完善。

Fractional-order calculus is about the differentiation and integration of non-integer orders. Fractional calculus (FC) is based on fractional-order thinking (FOT) and has been shown to help us to understand complex systems better, improve the processing of complex signals, enhance the control of complex systems, increase the performance of optimization, and even extend the enabling of the potential for creativity. In this article, the authors discuss the fractional dynamics, FOT and rich fractional stochastic models. First, the use of fractional dynamics in big data analytics for quantifying big data variability stemming from the generation of complex systems is justified. Second, we show why fractional dynamics is needed in machine learning and optimal randomness when asking: “is there a more optimal way to optimize?”. Third, an optimal randomness case study for a stochastic configuration network (SCN) machine-learning method with heavy-tailed distributions is discussed. Finally, views on big data and (physics-informed) machine learning with fractional dynamics for future research are presented with concluding remarks. https://www.mdpi.com/1099-4300/23/3/297/pdf