连续投影算法

NSIS jiemian仿酷狗安装包实例(Imitation cool dog package instance)

基于matlab，电力系统最优潮流问题，注释详尽(Based on matlab, optimal power flow problem, detailed comments)

基于matlab简单图像处理系统中对图片的取反功能(Based on a simple matlab image processing system for the inversion of the image)

用MATLAB去除移动车辆行驶过程的阴影，并对视频进行优化(Remove the shadow of the mobile vehicles using MATLAB, and to optimize the video)

介绍关于MATLAB的一些函数基本命令以及常用的处理图像方法(Introduced the MATLAB function basic commands as well as the commonly used image processing method)

function [H T] = Bretschneider(F,U,D) functie [H T] = Bretschneider(F,U,D) F= fetchlengte (m) U =windsnelheid (m/s) D= depth (m) Depth dependend Bretschneider formulag. see Sorensen, R.M. (1993). Basic Wave Mechanics for Coastal and Ocean Engineers. New York: John Wiley & Sons.

Hierarchical-Particle-Swarm-Optimization-Algorithm

该文针对具有两个相互重叠频率成分的密集频谱 ,分析了两个重叠频率成分在复频域的叠加情况 ,在不增加采样长度的条件下 ,通过向量分解和单频率成分的识别、校正方法 ,推导出其校正公式。(In this paper, with two overlapping frequency components of the dense spectrum of two overlapping frequency components in the frequency domain stacking situation, in terms of not increasing the sample length, through the vector decomposition and single-frequency components of the identification, correction derived the correction formula.)

用镜像矩阵求出矩阵的QR分解（正交三角分解），并求解线性方程组，该方法不必选主元，但其计算过程非常稳定。也可用于求矩阵的广义逆和求解线性最小二乘问题。子过程QRDCMP用镜像矩阵求m*n矩阵A的QR分解，A=Q^TR,其中Q是m*m正交矩阵，R为m*n上三角矩阵；子过程QRBKSB用矩阵的QR分解求解线性方程组Ax=b，其中A为n阶非奇异方阵。(Matrix obtained with the mirror matrix QR decomposition (orthogonal triangular decomposition), and solving linear equations, the method does not have to choose the main element, but its calculation process is very stable. Can also be used to find the generalized inverse matrix and solving linear least squares problems. Sub-process of the mirror matrix QRDCMP m* n matrix A QR decomposition, A = Q ^ TR, wherein Q is a m* m orthogonal matrix, R is m* n upper triangular matrix subprocess QRBKSB a QR decomposition to solve the matrix linear equations Ax = b, where A is non-singular square matrix of order n.)

This codes for Nonnegative Matrix Factorization Using ADMM