IM_1

fonction permet d extraire les fréquence de la transcription musicale

说明：  matlab代码，轴承特征提取，包括rms、最大幅值、峰值因子、绝对平均值、平均值、峭度、脉冲因子、裕度因子、能量，小波包、经典模态分解等特征(Matlab code, bearing feature extraction, including rms, maximum amplitude, crest factor, absolute mean, mean, kurtosis, pulse factor, margin factor, energy, etc.)

效率极高的基于delaunay三角网格剖分程序，只是没有图形输出，可以只将生成文件直接导入matlab中。(Based on highly efficient delaunay triangular mesh generation process, but there is no graphics output, you can only generate documents in directly into matlab.)

针对四维图像原始数据矩阵通过matlab程序画图(4D figure)

视频跟踪检测 背景核密度估计建模，欢迎指正，谢谢(Detection of the background video track modeling kernel density estimation, please correct me, thank you)

Akaike阶次辨识在有色噪声的情况下通过计算AIC的值得到最终的结果。(Akaike order identification in the case of colored noise by calculating the AIC' s worth to the final result.)

本代码可不用借助其他工具直接对光子晶体光纤的色散等直接计算，对学习pcf的朋友很有帮助！(This code can be without the help of other tools directly on the photonic crystal fiber dispersion and other direct calculation, learning pcf helpful friends!)

我写的一个小程序。用MATLAB自动生成任意维数和任意数量的数据，并且根据这些数据用一定的方法统计出这些点的概率密度。(I wrote a small program. MATLAB automatically generated using an arbitrary dimension and arbitrary amount of data, and based on these data in a certain way to the statistics of the probability density of these points.)

说明：  本目录主要包括：文档和两个源代码。 其中一个源代码是识别程序的，另一个是一个矩阵类库的，书里面也使用过，所以一并附上。 因为已经保存了训练好的网络权值，所以第一次使用识别程序时，可以直接运行\\Release目录下的可执行文件，然后对图片目录中的测试图片进行读入、识别。 当然读者也可以自行用训练样本训练网络，不过要特别注意训练样本的选择，否则可能造成识别率很低。训练样本选择的原则是，尽可能的有代表性，在训练时间不至于太长的情况下，训练样本数目尽量多。 ( This directory includes: documentation and two source code. One of the source code is to identify the procedure, the other is a matrix class library, the book which is also used, so be attached. Because it has saved the trained network weights, so the first use of identification procedures, you can directly run \ \ Release directory of the executable files, and then tested on the images directory to read pictures, identification. Of course, readers are free to use the training samples to train the network, but pay special attention to training samples, otherwise it may cause very low recognition rate. Training sample selection principle is that as far as possible, representative, in the long training time Buzhi Yu s case, the number of training samples as much as possible. )

solving 8 queen problem in matlab with GA