canny

企业信息交流系统(CICS)为企事业提供最新的资讯(Enterprise information exchange system (CICS) for the enterprises and institutions to provide the latest information)

一种层次聚类的方法，用matlab实现的源代码，可对点数据等进行聚类分析(A hierarchical clustering method, using matlab to achieve the source code, can be carried to the point of data clustering analysis)

commande d in pendule inversé par placement des poles

经典的灰度共生矩阵纹理计算方法，利用matlab针对图像进行马氏距离计算 ,本科毕设要求参见标准测试模型。( Classic GLCM texture calculation method, Using matlab to calcul)

现代控制原理作业 源程序 供参考 是MATLAB程序 有注释 (Modern control theory job source for reference)

包括：隐藏混沌序列即隐藏参数的生成；对图像进行隐藏；恢复出隐藏前置乱的目标图像；恢复出原目标图像；对隐藏目标置乱处理等(Include: hidden chaotic sequence that is hidden parameter generation images hidden the restoration of a hidden goal of arbitrary pre-image the restoration of the original target image to hide the goal of treatment, such as scrambling)

How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments. (How the K-mean Cluster workStep 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (Nk) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3. Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4. Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.)

series compensator facts devicesd

说明：  matlab 实现的蚁群算法,算法经过测试，用于非线性方程的优化求最值。(the implemention of anta algrithm by mtalab)

同步发电机短路分析,可以在示波器中看到结果(Synchronous generator short-circuit analysis。Can see the result on the oscilloscope)