调试成功的对PMSM算法的直接转矩控制测试例程

用LEVY法对系统进行参数辨识，利用实频响应与虚频特性来估计过程的传函。(LEVY method using the system parameter identification, the use of real and imaginary frequency characteristics of frequency response to estimate the process of transfer function.)

array weighting for Smart antennas

基于遗传算法的PID控制 用于优化求解控制器的参数 (based on genetic algorithms for optimizing PID control parameters Controller Solution)

MATLAB简单胞映射程序，修改原程序一些错误经调试，可以使用。(Simple cell mapping procedures, after debugging, you can use.)

正交匹配追踪，信号压缩传感的实现，可近似完全重构(Orthogonal matching pursuit)

太阳电池组件生产厂家通常仅为用户提供产品在标准测试条件(STC)下测出的Isc、Voc、Im、Vm、Pm值,本程序根据这些仅有的工厂测试数据在工程精度下复现光伏电池或之阵列在不同日射、不同温度下的I—V特性。(Solar module manufacturers generally only provide users with products under standard test conditions (STC) measured Isc, Voc, Im, Vm, Pm value, this program is just a plant based on these test data reproduced in the engineering precision PV battery or the array of different insolation, I-V characteristics at different temperatures.)

optimal placement dg with pso

2兆瓦异步双馈风力发电系统的建模与仿真，包含个子模块。pitch信号自己添加。。(2 MW doubly fed induction wind power system modeling and simulation, including the sub-modules. pitch signal to add their own. .)

ldpc编码，完整的编解码过程，并有多个编码实例(LDPC codes, the complete codec process and a number of coding examples)

函数实现了lelief算法。（计算样本的每一个特征的分类权重，选出具有最大权重的一组特征。样本的特征就是基因）。 对权重较大的一组基因进行两两冗余分析。将相关性弱的和强相关中权重大的基因保留，即为特征基因。 已知基因表达谱数据、不同类样本的个数，自行设定分类特征的权重阈值。 对原始数据标准化的方法：（x－基因均值）/基因方差。 样本的类内类间距离采用欧氏距离。(Lelief function implements the algorithm. (Classification weight each feature samples is calculated weight of a selected set of features having the greatest weight. Characteristic is the gene sample). Of the weight of a larger set of pairwise genetic redundancy analysis. The significant correlation between weak and strong correlation in the right gene retention, that is characteristic gene. Number of known gene expression data, samples of different classes, wherein the classification set threshold own weight. Of raw data standardized methods: (x- Gene mean)/variance gene. The between-class distance class of the sample using the Euclidean distance.)