Energy_detection_Threhsold_finding_monte1

张雄的无网格法这本书中的所有程序的引用目录，使得书本的程序结构更加简明。(Zhang Xiong of the meshless method that all the procedures in this book reference directory, the program structure makes the book more concise.)

说明：  matlab使用垂直Sobel算子，自动选择阈值 [VSFAT Threshold]=edge(f, sobel , vertical ) 边缘探测 figure,imshow(f),title( 原始图像 ), 显示原始图像 figure,imshow(VSFAT),title( 垂直图像边缘检测 ) 显示边缘探测图像 使用水平和垂直Sobel算子，自动选择阈值 SFST=edge(f, sobel ,2) figure,imshow(SFST),title( 水平和垂直图像边缘检测 ) 显示边缘探测图像 使用指定45度角 Sobel算子滤波器，指定阈值 s45=[-2 -1 0 -1 0 1 0 1 2] SFST45=imfilter(f,s45, replicate ) SFST45=SFST45>=2 figure,imshow(SFST45),title( 45度角图像边缘检测 ) 显示边缘探测图像 (matlab I=rgb2gray(I0) J0=double(I) [VSFAT Threshold]=edge(f, sobel , vertical ) figure,imshow(f),title figure,imshow(VSFAT),title)

当配电网中含有多个电源时，传统的适用于辐射网的潮流程序无法使用，本篇为包含供电区域的自动划分的配电网潮流计算(When a distribution network comprising a plurality of power can not be used to apply the traditional trend of net radiation procedures herein, this automatic power flow calculation for the division include the supply area)

利用kalman滤波算法对状态空间描述的位移测量系统进行了滤波处理，对系统输出的真实位移、测量位移和滤波位移进行了对比，显示了kalman滤波算法较好的滤波性能。(Displacement measurement system described by the equation of states were filtered by Kalman filter algorithm. The output of the system, including the real displacement, measuring displacement and filtering displacement were compared, and the results showed the great performance of Kalman filter algorithm.)

Computer Vision resource code in matlab

DATA CLUSTERING USING HIEARAACHICAL TECH IN MATLAB

Solutiona Manual Andrea Goldsmith Wireless Communications

matlab file newly created

用于简单函数优化的算法代码（MATLAB）,希望对大家有用 (For simple function optimization algorithm code (MATLAB)。I need it can be useful to you)

说明：  matlab实现：①递推增广最小二乘参数估计（RELS）②确定性系统的递推梯度校正参数估计（RGC）③递推最小二乘参数估计（RLS）④递推极大似然参数估计（RML）⑤递推随机牛顿参数估计（RSNA）(Matlab: (1) augmented recursive least square parameters estimation (RELS) (2) of a deterministic system recursive gradient correction parameter estimation (RGC) (3) recursive least squares (RLS) (4) parameter estimation, the recursive maximum likelihood parameter estimation (RML) (5) recursive random Newton parameter estimation (RSNA) )