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so what should i write, im tired of writting

基于MATLAB的非线性方程二分法求解。(bisection method)

一个动态copula的例子，利用patton2004,2006a，2006b中的方法(example for dynamic copula)

nonmaxsup——非最大值抑制 hysthresh——设定阈值区间，返回一个二值化图像 canny——边缘探测，图像边缘增强 adjgamma——调整图像的伽马值 findline——利用线性Hough变换和Canny边缘探测得到的线上各点的坐标 circlecoords——返回由圆的半径和圆心坐标决定的圆上各点像素的坐标 houghcircle——取一幅经过canny变换的图像，利用hough变换找到图像中的一个圆 findcircle——计算所得线上各点的坐标归纳出一个圆的半径和圆心，确定该圆的各点坐标 gaborconvolve——利用一维盖伯滤波器对图像进行处理 gethammingdistance ——返回两幅虹膜图像提取的特征码之间的海明距离 linecoords——返回一条线的上各点的x,y坐标值(nonmaxsup- non-maximum suppression hysthresh- set the threshold range, returns a binary image canny- edge detection, image edge enhancement adjgamma- adjust the image' s gamma value findline- linear Hough transform and Canny edge detection get the coordinates of each point circlecoords online- Returns coordinate houghcircle on the circle of the radius and center coordinates of the points decision pixels- After taking a picture canny transformation, using hough transform to find the image of a circle findcircle- the calculated coordinates of each point line summed up a circle of radius and center, to determine the coordinates of each point of the circle gaborconvolve- using a 维盖伯 filter for image processing gethammingdistance- returns two iris images extracted linecoords Hamming distance between the signature- a return line to the points on the x, y coordinate values)

基于多线程机制的，利用Matlab编写，粒子群优化算法。目标变量采用归一化处理，适用于所有的优化函数。优化函数自定义为fitness(x)。(Based on multi-threading mechanism, the use of Matlab to prepare, particle swarm optimization algorithm. Target variables using normalized treatment applies to all of the optimization function. Since the optimization function is defined as fitness (x).)

说明：  bp神经网络预测程序，可用于与小波神经网络对比(BP Neural Network Prediction Program, which can be used to compare with Wavelet Neural Network)

说明：  matlab 应用举例(Application examples matlab)

this is exemple simple modulation psk and bpsk

均匀线列阵波束形成，使用契比雪夫等旁瓣加权方式(chebshev different sidelobe)

是关于QPSK的一篇文章,对研究QPSK很有帮助的(Is an article on the QPSK, QPSK useful for research)