Plsgui

说明：  压缩包里包含了无约束优化问题常用的几种求解方法的源程序：变量轮换法（variable_rotation.m）、最速下降法（steepest_descent.m）、修正牛顿法（modified_newton.m）、共轭梯度法（conjugate_gradient.m）。另外，coefficient_matrix.m为目标函数系数获得矩阵，minval.m为最小值计算函数，gradient.m为梯度计算函数(Compression bag contains unconstrained optimization problems of several commonly used method of source: variable rotation Act (variable_rotation.m), steepest descent method (steepest_descent.m), as amended Newton (modified_newton.m), conjugate gradient method (conjugate_gradient.m). In addition, coefficient_matrix.m as the objective function coefficients obtained matrix, minval.m function for the minimum calculation, gradient.m for gradient calculation function)

整体最小二乘最小奇异值法的matlab实现，供大家一块学习(The total least squares minimum singular value method of Matlab implementation, for everyone to learn a piece)

Using the nearest neighbor algorithm for clustering and classification of random samples and calculate the classification rate, compared to the algorithm including modified versions

it s a code for frequency hopping

本书描述了matlab的一些使用方法和对一些算法的简要介绍(This book describes some use matlab and a brief description of some algorithms)

栅栏效应matlab 编程，栅栏效应matlab 编程。栅栏效应matlab 编程。(Fence effect matlab programmin)

基于块的解扩重扩多目标算法性能--Block Based RLS De-spread Re-spread Multitarget Array Algorithm and Performance (Block Based RLS De-spread Re-spread Multitarget Array Algorithm and Performance )

精通MATLAB与C和C++混合程序设计第一章(Proficient in MATLAB and C and C++ hybrid program)

一个m函数，可以读取GprMax2d的模型数据，将雷达正演模拟的模型的刨面数据读出来(A function of m, can be read GprMax2d model data, radar forward simulation model of the planing surface data read out)

用K均值算法和C模糊算法对sonar数据和iris数据进行分类。 K均值算法是一种很常用的聚类算法，其基本思想是，通过迭代寻找K个聚类的一种划分方法，使得用这K个聚类的均值来代表各类样本是所得到的的总体误差最小。 模糊C均值（FCM）算法在K均值算法的基础上，用模糊子集代替确定子集，从而得到模糊的分类结果，即分类结果的模糊化。(Sonar data and iris data are classified by means of K mean algorithm and C fuzzy algorithm. The K mean algorithm is a very common clustering algorithm. Its basic idea is to find a partition method of K clustering by iteration, so that the average error of the mean of the K clustering is minimized. The fuzzy C mean (FCM) algorithm is based on the K mean algorithm. The fuzzy subset is replaced by the fuzzy subset, thus the fuzzy classification result is obtained, that is, the classification result is fuzzed.)