MATLAB

传统的kmeans聚类算法不能保证时间序列聚类结果的时序性；基于warp-kmeans聚类算法可以有效处理时间序列的聚类问题，而且复杂度低，迭代次数少。 ，输出有目标函数在每次迭代后的值，聚类中心以及聚类区间。内有测试数据和相关文献，点击 test.m 可以完美运行(The traditional kmeans clustering algorithm can not guarantee the time series of the time series clustering results. The warp-kmeans clustering algorithm can effectively deal with the clustering problem of time series, and the complexity is low, and the number of iterations is less. The output has the value of the target function after each iteration, the clustering center and the clustering interval. There are test data and related documents, click test.m can be perfect operation.)

说明：  微分进化算法可以求解大规模非线性的数学模型(Differential evolution algorithm)

介绍了PSCAD基本的模块和各个部分的功能，并提供了一些具体的例子可以进行操作练习。(PSCAD introduced the basic modules and functions of various parts, and provides some specific examples of practice can operate.)

基于ＰＩＤ的性能监测与评估技术，但是是单个ＰＩＤ的．多回路的暂时没有找到．(PID-based performance monitoring and assessment techniques, but it is of a single PID. Multi-loop did not find the time being.)

Gabor filters image processing

说明：  A New Fuzzy Fault Locator for Series Compensated Transmission Lines

This method usually increases the global contrast of many images, especially when the usable data of the image is represented by close contrast values. Through this adjustment, the intensities can be better distributed on the histogram. This allows for areas of lower local contrast to gain a higher contrast. Histogram equalization accomplishes this by effectively spreading out the most frequent intensity values.

极大似然估计器用于简单通信系统模拟,估计A1,A2: s1 = x11*A1 + x12*A2 s2 = x21*A1 = x22*A2 r1 = s1 + n1 r2 = s2 + n2(Maximum likelihood estimator for a simple communication system simulation, it is estimated that A1, A2: s1 = x11* A1+ x12* A2 s2 = x21* A1 = x22* A2 r1 = s1+ n1 r2 = s2+ n2)

多种模式识别算法的编程实现，非常详细，包括PCA，MPCA，LLE等(Several pattern recognition algorithm is introduced, including PCA, MPCA, LLE etc.)

用于matlab 的学习，前五章内容为基本介绍，包括软件安装与卸载，数据类型，数组与matalab常用功能(For the matlab learning, basic introduction to the first five chapters content, including software installation and uninstallation, data types, arrays with common functions matalab)