FSK

AT88 PROGRAMMER DIAGRAM

matlab环境下模拟单服务台排队，通过程序设置到到银行排队办业务的人的人数及时间间隔，计算平均每个人需要等待的时间。(set the number of the queue，and the time between each comer ,it will calculate the average waiting time of each person)

vibration analysis of induction motor

Scatter plot for large data set (tested for 10 million points)

用于建立主成分分析模型，计算两个矩阵之间的欧氏距离，包括数据分析、绘图等等。( Principal component analysis model for establishing, Calculation of the Euclidean distance between the two matrices, Data analysis, plotting, etc..)

svm的一种特征选择方法，基因选取算去，减少特征数量，减少运算时间，也可提高运算精度(svm a feature selection method, gene selection operator to reduce the number of features to reduce the computation time, but also can improve the calculation accuracy)

精通MATLAB数字图像处理与识别 chapter4 代码(Proficient in MATLAB digital image processing and recognition chapter4 code)

Control DC Motor via Matlab simulation

基于二值化图像的图像分割及分类识别 (Based on the binary image segmentation and classification of image recognition )

聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)