finalstage1

几个指向性的程序，包括线阵，面阵和带加权的阵型()

用矩量法计算半波振子的电流分布、输入阻抗、E面方向图。(Calculated half-wave dipole moment method using the current distribution, input impedance, E plane patterns.)

传统标准支持向量机SVM方法用于分类的matlab代码，可以直接在matlab中运行，具体操作参看http://www.matlabsky.com/thread-10313-1-1.html中的系列教程，这里主要考虑的是支持向量机用于分类的情形，有需要的同学可以下载学习，欢迎大家一起交流共同进步。

A simulation of PLL using MS EXCEL..... very handy contains 3rd order as well as 4th order PLL simulations and is presented in a very easy to understand manner.

多尺度LBP，代码根据论文“Learning Multi-scale Block Local Binary Patterns for Face Recognition”编写的(this code is obtained from the paper named "Learning Multi-scale Block Local Binary Patterns for Face Recognition")

（1）计算图像中每个像素点的LBP模式(等价模式,或者旋转不变+等价模式)。 （2）然后计算每个cell的LBP特征值直方图，然后对该直方图进行归一化处理(每个cell中，对于每个bin,h[i]/=sum,sum就是一副图像中所有等价类的个数)。 （3）最后将得到的每个cell的统计直方图进行连接成为一个特征向量，也就是整幅图的LBP纹理特征向量； 然后便可利用SVM或者其他机器学习算法进行分类识别了。((1) calculate the LBP pattern of each pixel in the image (equivalent mode, or rotation invariant + equivalent mode). (2) then the LBP eigenvalue histogram of each cell is calculated, and then the histogram is normalized (for each cell, for each bin, h[i]/=sum, sum is the number of all the equivalent classes in a pair of images). (3) finally, the statistical histogram of each cell is connected into a feature vector, that is, the LBP texture feature vector of the whole picture. Then, SVM or other machine learning algorithms can be used for classification and recognition.)

说明：  本文是关于在声波信号处理领域极为流行的S变换数学理论，英文版，仅供参考(This article is about the most popular acoustic signal processing, mathematical theory of S-transform, in English, for reference only)

matlab 并行工具包 parfor spmd 等多核并行工具包使用方法(matlab parallel toolkit parfor spmd such as the use of multi-core parallel toolkit)

利用最小二乘法进行拟合多元非线性方程，MinkowskiMethod算法 ,最终的权值矩阵就是滤波器的系数，包括AHP，因子分析，回归分析，聚类分析，信号维数的估计，用MATLAB实现动态聚类或迭代自组织数据分析。

TI公司的交流电机控制仿真的Matlab程序,很有用的啊,大家快下吧(AC motor control simulation of the Matlab program, very useful ah, everyone under the bar fast)