guanghuabi

现代通信系统matlab源代码，通信的肯定用得着的(Matlab source code for modern communications systems, communication certainly useful in the)

这是一段用于谱分析算法中的求蝶形算子的 子程序，此程序采用C语言编写，移植性比较强(This is a period for the spectral analysis algorithm for the subroutine butterfly operator, this procedure using C language, the transplantation of relatively strong)

说明：  一些有关最优控制理论的控制实例程序集和仿真 (Control instance assembly of the optimal control theory and simulation)

这篇文章是盲信号处理，因为是英文文章，所以大家看内容就好了。(Principal component analysis (PCA) is a mainstay of modern data analysis- a black box that is widely used but poorly understood. The goal of this paper is to dispel the magic behind this black box. This tutorial focuses on building a solid intuition for how and why principal component analysis works furthermore, it crystallizes this knowledge by deriving from simple intuitions, the mathematics behind PCA . This tutorial does not shy away from explaining the ideas informally, nor does it shy away from the mathematics. The hope is that by addressing both aspects, readers of all levels will be able to gain a better understanding of PCA as well as the when, the how and the why of applying this technique.)

说明：  聚类算法MATLAB程序实现，聚类（Cluster）分析是由若干模式（Pattern）组成的，通常，模式是一个度量（Measurement）的向量，或者是多维空间中的一个点。聚类分析以相似性为基础，在一个聚类中的模式之间比不在同一聚类中的模式之间具有更多的相似性。(DBSCAN_Clustering Algorithm)

vc和matlab混合编程，调用matlab强大的计算数学库(vc and mixed matlab programming, matlab call powerful computational mathematics library)

一个DLAN的例子，非常的有意思，希望能够有帮助(An example of a DLAN, very interesting, hope to be able to help)

基于矩量法仿真的笼形天线宽带化设计 (Method of Moments simulation cage antenna design is based on broadband)

说明：  VB调用MATLAB 使用VB来调用matlab里的函数，可以综合matlab的强大功能使vb开发的程序效率更高。(MATLAB using VB to call matlab in VB to call the function, can be integrated so that the power of matlab programs vb efficient.)

梯度下降法是最早最简单，也是最为常用的最优化方法。梯度下降法实现简单，当目标函数是凸函数时，梯度下降法的解是全局解。一般情况下，其解不保证是全局最优解，梯度下降法的速度也未必是最快的。梯度下降法的优化思想是用当前位置负梯度方向作为搜索方向，因为该方向为当前位置的最快下降方向，所以也被称为是”最速下降法“。最速下降法越接近目标值，步长越小，前进越慢。(The gradient descent method is the earliest and most simple and most commonly used optimization method. The gradient descent method is simple to realize. When the objective function is a convex function, the solution of the gradient descent method is a global solution. In general, the solution is not guaranteed to be the global optimal solution, and the gradient descent method is not necessarily the fastest. The optimization idea of gradient descent method is to use the current position negative gradient direction as the search direction, because the direction is the fastest descending direction of the current position, so it is also called the steepest descent method. The faster the slowest descent approach is closer to the target, the smaller the step, the slower the progress.)