一个好的香农能量算法，matlab程序

说明：  用MATLAB读取bmp图片 同时得出三维的坐标 同时绘制了灾区地震的地形图(Bmp image to use MATLAB to read at the same time to draw three-dimensional coordinates of the earthquake disaster areas at the same time drawing the topographic map)

reey application demo and usage

使用matlab中快速傅里叶变换fft实现滤波(The use of the MATLAB FFT FFT filter)

这是牛顿-拉弗逊 潮流计算程序，用Matlab实现，可用(This is the Rafferson Newton power flow calculation program, using Matlab to achieve, can be used)

平面均匀线阵的阵列波束形成方法和平面阵的阵列方向图(ULA plane array beamforming methods and planar array array pattern)

关于超声波倒车雷达测距的，处理信号的时频分析，借鉴了主成分分析算法（PCA），毕业设计有用，采用波束成形技术的BER计算，外文资料里面的源代码。

本程序提供主成分分析算法，该算法有四个小程序组成，简单，实用。(This program provides the main element analysis of the algorithm, the algorithms are four small and simple, practical. )

聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)

说明：  通过编程实现通过共轭梯度法和Gauss-Seidel迭代法两种方法求解方程组(By programming through the conjugate gradient method and Gauss-Seidel iteration method for solving equations of two)

hough变换检测直线代码在matlab下的运行(hough transformation)