MEAN_ratio

图像识别的小软件，识别率还算凑合吧，大家共同学习(Small image recognition software, the recognition rate still make it, we learn together )

实现对酒瓶子的边缘检测，背景差分，垂直和水平投影等，并可实现计数功能。(Achieve the bottles of edge detection, background difference, the vertical and horizontal projection, and to achieve counting.)

一种细化的骨架提取算法 可以提高徐璈的处理厚重图像(sgsdgsdgsdgggs skeleton extraction)

说明：  用c写的jpg编解码，包括jpeg2bmp和bmp2jpeg，可在vc6下调试。(With c written jpg codec, including jpeg2bmp and bmp2jpeg, may be under vc6 debugger.)

PCA+LDA人脸识别，识别率高于单独PCA或LDA算法。需要matlab dimension reducation toolbox。(Face verification using PCA and LDA fusion. Better performance than single PCA or LDA algorithm. The image database is included. Matlab dimension reduction toolbox is requrired. )

随机中点位移法模拟分形地形的MATLAB源代码，用于分形几何，实用！(Random midpoint displacement fractal terrain simulation of MATLAB source code for the fractal geometry, and practical!)

这个代码可以获取一种颜色可以生成10进制的数，和一个16进制的数(the code can get a color can generate 10 to the 229 number, and a few of the 229 16)

可以在程式畫面上任意畫圖寫字並且可清除再任意使用(Can any drawing program screens and write and to clear any longer use)

介绍了DAB 接收机中的OFDM 同步算法，重点对OFDM 接收机方案中基于保护间隔的符号定时估计、频 率偏移估计进行了分析，提出了适用于Eureka147DAB 系统的同步算法；并对各种算法进行了计算机仿真，本文介绍的算法满 足DAB 接收机的要求，有很大的应用价值。(Introduced the DAB the OFDM receiver synchronization algorithms, focusing on OFDM receiver scheme based on the protection of the interval estimation, frequency symbol timing Rate migration estimates are analyzed and some appropriate Eureka147DAB system in the synchronization algorithms And kinds of the computer simulation algorithm, this paper introduces the algorithm of the full The requirements of the foot DAB receiver, a large application value. )

矩形信号的frft（分数傅里叶变换wigner_ville_1.m 单分量信号去噪 wigner_ville_2.m 双分量平行信号去噪 wigner_ville_3.m 3分量信号频率检测）分数傅里叶变换是经典傅里叶变换的另一种改进方式。它的主要特点是提供研究对象从时间域到频率域全过程的综合描述，随着阶数从0连续增长到1，分数傅里叶变换展示出研究对象从纯时间域逐步变化到纯频率域的所有变化特征。因此，分数傅里叶变换提供了远比傅里叶变换多得多的可供选择的数据处理和分析方法。(The rectangular signal FRFT (Fractional Fourier Transform) Score Fourier transform is another modification of the classic Fourier transform. Its main feature is a comprehensive description of the study from the time domain to the frequency domain, with the order of continuous growth from 0 to 1, the fractional Fourier transform demonstrate the object of study from a purely time-domain gradually change to a pure frequency domain variation. Thus, the fractional Fourier transform provides data processing and analysis methods than Fourier transform much more to choose from.)