Gaussian_propagation

This is an .m file to use in power system state estimation problems. It has no restriction on the number of network parameters and you only have to follow the format for input data and interpret the output data accordingly. There is a pdf File in spanish explining all the basics of this code. I will try to get an english version ready asap.

集员仿射投影算法的matlab码源，论文Set-Membership Affine Projection algorithm的仿真程序(Set membership affine projection algorithm)

卡尔曼滤波器的经典介绍。非常详细，通俗易通，中文版本(Classic introduction to the Kalman filter. Very detailed, popular ETS, Chinese version)

基于matlab的AGC程序，供参考使用。(Based on the matlab the AGC program for reference use.)

自由电子激光，一维SASE理论，matlab模拟(free-electron laser, a peacekeeping SASE theory, Matlab simulation)

本程序适用于论文metasample-based sparse representation for tumor classification(this code suite for paper metasample-based sparse representation for tumor classification)

matlab中图形的边缘检测，然后进行角点获取(edge detect and corners acquisition)

约束优化问题： minRosen(Rosen梯度法求解约束多维函数的极值)(算法还有bug) minPF(外点罚函数法解线性等式约束) minGeneralPF(外点罚函数法解一般等式约束) minNF(内点罚函数法) minMixFun(混合罚函数法) minJSMixFun(混合罚函数加速法) minFactor(乘子法) minconPS(坐标轮换法)(算法还有bug) minconSimpSearch(复合形法)(Constrained optimization problem: minRosen (Rosen gradient method for solving constrained multi-dimensional function of extremes) (algorithm also bug) minPF (solving linear equations outside the penalty function method constraints) minGeneralPF (outside the penalty function method for solving general equality constraints) minNF (internal penalty function method) minMixFun (mixed penalty function method) minJSMixFun (mixed penalty function acceleration method) minFactor (multiplier method) minconPS (coordinate rotation method) (algorithm also bug) minconSimpSearch (complex method))

matlab mdl 的卡尔曼滤波程序清晰简洁(matlab mdl Kalman filtering procedures clear and concise)

用于建模数据分集。计算各样本点的欧式距离，首先将距离最大的两个点放入第一个样本集，接着将余下距离最大的两个点放入第二个样本集，依次计算，将剩余数据点分别放入上述两个样本集。( This algorithm starts by selecting the two points furthest from each other (euclidean distance) and puts them both in a first set. Then the next two points furthest from each other are put in a second set, and the procedure is continued by alternatively placing pairs of points in the first or second set. For calibration applications, the second set can be the test set, and the calibration would be the concatenation of the first set plus the remaining samples.)