GA--MATLAB

COFDM diseñ o y simulacion

实现基于PSO的混合粒子优化算法,具有很好的稳定性和快速性(Search algorithm based on hybrid particle swarm optimization algorithm based on TSP)

说明：  基于蚁群算法的路径分析，用 matlab工具实现 每个模块都是详细分块写的(Based on path analysis of ant colony algorithm, each module is written in detail by block using MATLAB tool.)

The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order (The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order)

这是一个有关电力电子的simulink仿真实例(This is a power electronics simulink simulation examples)

说明：  基于fuzzy c-means（FCM）的无监督模糊聚类算法，输出值有：各个样本的类别标签、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data.mat，点击 test.m 可以完美运行。(The unsupervised fuzzy clustering algorithm based on fuzzy c-means (FCM) outputs the class labels of each sample, the value of the target function after each iteration, the clustering center and the clustering interval. There is test data ('data.mat') inside, click ' test.m' to be able to run perfectly.)

牛顿迭代法求非线性方程的解，需输入初始值，方程，导数方程，步数，error(Newton iteration solution of nonlinear equations required to enter the initial value equation, derivative equation, step number, error)

对M=16的PSK系统仿真，分析系统的误码率，画出仿真误码率曲线，与理论误码率曲线进行对比。（MATLAB语言实现）(M = 16 for the PSK system simulation, analysis of system bit error rate, BER simulation draw curves with the theoretical BER curves are compared. (MATLAB language))

constract decring of image

区域生长分割 matlab 手动点击设定种子点(Click on region growing segmentation matlab manual seed point set)