Matlabmodelingtoolbox

GRAM SCHMDIT PROCESS matlab code

Changing the polar circle density

说明：  copula代码实现经验copula与copula的欧氏距离的计算(copuladaimanenggoushixianoushijulidejisuan)

The least square method, recursive calculation

本程序在Matlab环境下完成，用于边缘的亚像素定位，精度达到0.1-0.2个像素，内含源代码及说明(This program completed in the Matlab environment. It is used for sub-pixel edge positioning and the accuracy of the method is 0.1-0.2 pixels. Including the source code and description.)

可以用来计算分歧度，这个分析度是信息论中的一个概念，类似于熵。(we can use it to calculate the klsym divergence)

说明：  IEEE 30 BUS TEST SYSTEM,可运行(IEEE 30 BUS TEST SYSTEM, and it can be succesfully used.)

维纳滤波,可以有效的对信号进行白噪声的滤除(weina filter)

this is a simple function for convert into Cartesian to polar coordinates and adding two functions

Source separation problems in digital signal processing are those which are used to separate useful signal a mix of signals of interest, other signals and noise. The typical example of a source separation problem is the cocktail party problem, where many number of peoples are talking simultaneously in a room and a listener is trying to follow one of the discussions. The human brain can separate the voices of different people (source separation) using neurons in the auditory region. But source separation using digital signals is difficult task with the available techniques. Several approaches have been proposed for solving this issue but most of the techniques are still in development stages. Some of the successfully tested approaches are principal components analysis (PCA) and Independent components analysis (ICA). Both the approaches work well when there are no delays or echoes present