matrixqueue

Krylov subspace作为一种迭代方法，在求解非线性方程组方面发挥巨大作用，这个ppt和大家分享(Krlov subspace method)

Iterative Closest Point (ICP) 算法的改进型，精读高于原始版的，对点云噪声和漏洞的处理效果更好于原始版。(Iterative Closest Point (ICP) algorithm is improved, intensive than the original version.)

LMF波形的模糊函数，用matlab编写。(LMF waveform ambiguity function, written with matlab.)

this code is for Object Co-Segmentation Based on Shortest Path Algorithm and Saliency Model paper. I used this code and it was correct and make true answers.

design of flyback converter

随机森林算法的matlab代码，这里旨在给初学者研究的随机树回归算法(Random forest algorithm Matlab code, aimed at beginners study a random tree algorithm)

achartengine 动态折线图的实现(Realization of dynamic line graph achartengine)

说明：  clc; clear all; close all; [filename, pathname, filterindex] = uigetfile({'*.jpg;*.tif;*.png;*.gif','All Image Files';... '*.*','All Files' }, '选择待处理图像', ... 'images\01.jpg'); file = fullfile(pathname, filename);%文件路径和文件名创建合成完整文件名 id = Get_Id(file);%得到file中的所有对象 Img = imread(file);%根据路径和文件名读取图片到Img [Plate, bw, Loc] = Pre_Process(Img); % 车牌区域预处理 result = Plate_Process(Plate, id); % 车牌区域二值化处理 % 寻找连续有文字的块，若长度大于某阈值，则认为该块有两个字符组成，需要分割 bw = Segmation(result); words = Main_Process(bw); % 主流程处理 Write_Mask(words, id); % 写出到模板库 str = Pattern_Recognition(words); % 识别(Mike is a student. He is my good friend. He is busy at the weekend. He is going to read a magazine this Saturday morning. He is going to go to the zoo this Saturday afternoon. He is going to buy a book this Sunday morning. He is going to learn Kungfu this Sunday afternoon. He is going to watch TV this Sunday evening.)

工程计算可视化与MATLAB实现:本书列举了大量的算例，并附有数值解和图形解，使学生通过上机学到数学和相关领域的知识。(Engineering Computing and Visualization in MATLAB: This book lists a number of examples, along with numerical and graphical solution, so that students learn mathematics through the machine and the related fields of knowledge.)

alpha稳定分布的函数。该分布是一种连续概率分布，其概率密度比高斯分布概率密度有更厚的拖尾，是一类适用范围很宽的随机信号模型，比高斯分布有更广泛的适用性。(Alpha stable distribution function. This distribution is a continuous probability distribution, the probability density are thicker than gaussian probability density trailing, random signal model is a kind of very wide application scope, has wider applicability than gaussian distribution. )