DE_8PSK

mtsp解决方案的matlab求解，可以很好的解决多旅行商的tsp问题(mstp solution matlab solving Can solve the multiple traveling salesman tsp)

常见的潮流程序主要采用直角坐标来进行，本程序采用极坐标对简单输电网系统潮流进行计算(Common trend of the procedure used mainly for rectangular coordinates, polar coordinates, the program uses a simple grid system to calculate the trend)

一个OFDM系统的仿真程序。里面有程序的详细说明(An OFDM system simulation program. There are procedures for a detailed description of)

该函数实现扩展卡尔曼滤波算法，用于非线性状态估计，目标跟踪(EKF filter)

旅行商问题，相信学过数学建模的人都知道吧。需要的下载一下吧。(The traveling salesman problem, believe that the learned mathematical modeling people know it. Need to download it.)

异步时间序列处理领域的动态时间弯曲算法（DTW），基于matlab开发(Dynamic time warping(DTW) algorithm of asynchronous time-series processing field , developed on matlab)

总图专业平面布置优化程序 输入数据物流流进厂房标号 物流关系数 物流关系标号 物流强度 根据matlab双目标优化算法计算最优平面布置方案(The total figure of professional input data layout optimization program logistics logistics flows into the plant label relationship between the number of logistics logistics strength label matlab dual-objective optimization algorithm based on calculating the optimal layout of the program)

this program is for bwfw power flow.

这是一个关于稀疏高斯过程的matlab源码，可以用于计算测试输入的高斯预测值。( spgp_pred computes the SPGP predictive distribution for a set of test inputs. You need to supply a set of pseudo-inputs or basis vectors for the approximation, and suitable hyperparameters for the covariance. You can use any method you like for finding the pseudo-inputs , with the simplest obviously being a random subset of the data. It is coded for Gaussian covariance function, but you could very easily alter this. It is also fine to use for high dimensional data sets. spgp_lik is the SPGP (negative) marginal likelihood and gradients with respect to pseudo-inputs and hyperparameters. So you can use this if you wish to try to optimize the positioning of pseudo-inputs and find good hyperparameters, before using spgp_pred . I would recommend initializing the pseudo-inputs on a random subset of the data, and initializing the hyperparameters sensibly. Its current limitations are that 1) it is slow and memory intensive for high dimensional data sets 2) it is heavi)

本资料是关于MST_Kruskal算法的matlab实现程序(MST_Kruskal matlab)