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一个简单的matlab遗传算法，实现数的平方最优值(a simple genetic algorithm implemented by matlab to solve the optimization of the data square)

说明：  图论中用得最多的最短路算法即Dijkstra，与Floyed算法。(Graph Theory with most that is the most short-circuit algorithm Dijkstra, and Floyed algorithm.)

Matlab codes for random matrix theory.

这是一个把神经网络直接应用于轴承的故障诊断的程序，输入轴承的信号，直接得答案(This is a direct application of neural network in bearing fault diagnosis procedures, input bearing signal, a direct answer)

matlab 图片的除噪，先给图片添加椒盐早上，后通过中值滤波，除掉噪声(matlab image noise removal, give the picture to add salt and pepper in the morning, after the adoption of the median filter to get rid of the noise)

Devkit8600 AM3359配套的资源开发包,可以再裸机环境下快速运行该程序平涂AM3359外设功能。(Devkit8600 AM3359 SDK)

遗传算法matlab程序，适合初学者，请大家指教(Genetic algorithm matlab program, please advise)

图片印刷字符的识别（可识别多种字体） 将Matlab工作空间路径设置为本文件夹 在Matlab命令窗口内输入： numCongnition( able1/01.jpg ) 通过改图片来对不同的图进行处理，其中able1,able2,able3三个文件夹分别对应三种字体 命令窗口输出要识别的字符，并且自动弹出中间处理过程窗口 也可以运行： num = pretreat( able1/01.jpg ) imshow(num) 直接得到预处理后的图片 再键入： getNumber(num) 得到字符输出 (Set the Matlab workspace path to this folder In the Matlab command window input: NumCongnition ( able1/01. JPG) Through change pictures to deal with different figure, including able1, able2, able3 three folders corresponding to three kinds of fonts Command window output to identify characters, and automatically process among popup Windows Can run: Num = pretreat ( able1/01. JPG) Imshow (num) Directly after preprocessing of images Type: GetNumber (num) Get the output character)

knn是一种分类算法，它是基于matlab的一种模式识别的经典算法，一般适用于样本个数较小的样本分类。(KNN, it is classification algorithm based on matlab a pattern recognition of the classic algorithm, generally applied in sample number of smaller sample classification. )

信号去噪的基本步骤： （1）信号的小波分解； （2）小波分解高频系数的阈值量化； （3）信号的小波重构。使用分解的低频系数以及阈值量化后的高频系数进行小波重构。 (The basic steps of signal denoising:( 1) of the wavelet decomposition of signals ( 2) the high frequency coefficients of wavelet decomposition threshold quantization ( 3) the signal wavelet reconstruction. Using the decomposition of the low frequency coefficient and threshold quantization the high-frequency coefficient after wavelet reconstruction.)