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实现对任意多边形的三角形凸分解。(To realize arbitrary triangle polygon convex decomposition.)

分形维数计算的毯子算法matlab代码，有一定借鉴意义(Calculation of the fractal dimension of the blanket algorithm matlab code, there is a certain reference)

分形图形的生成源程序，生成不同参数的Mandelbrot集和Julia集，对分形的初学者学习的好帮手。(fractal graphics generation source. Generation different parameters of the Mandelbrot set and Julia sets. Fractal of the beginners learn the good helper.)

只适用于时间序列的matlab下的分形维数计算的代码(Applies only to the time series under matlab fractal dimension calculation code)

WXH-斐波那契数列.Koch曲线 动态的Von Koch分形曲线,中点法生成Sierpinski地毯 分形蝴蝶 (WXH-Fibonacci sequence. Koch curve dynamic Von Koch fractal curve, the mid-point method to generate fractal Sierpinski carpet Butterfly)

两个matlab程序，一个实现图像的桶型畸变（Barrel Distortion），另外一个可以还原已经桶形畸变的图像(Two matlab programs,one is able to translate picture to Barrel Distortion.the other can return the translated picture.)

求故障树的 1）对偶树； 2）最小割级和最小路集； 3）假定底事件的故障概率已知，求顶事件发生的概率； 4）求底事件的结构重要度、概率重要度和关键重要度。(Seeking Fault Tree 1) dual tree 2) minimum cut level and minimal path sets 3) It is assumed that the end of the event of the failure probability known, find the probability of occurrence of the top event 4) Evaluate the end of the event structure importance, important degree of probability and critical degree.)

图像复式，自己调试通过的，与大家交流学习(Image duplex, adopted their own debugging, and to share their learning)

Diffusion-limited  Aggregation（DLA）扩散限制凝聚，是由Witten和Sander于1981年共同提出来的。其基本思想是：首先置一初始粒子作为种子，在远离种子的任意位置随机产生一个粒子使其做无规行走，直至与种子接触，成为集团的一部分。然后再随机产生一个粒子，重复上述过程，这样就可以得到足够大的DLA团簇。(Diffusion-limited Aggregation (DLA) Diffusion Limitation Cohesion was presented by Witten and Sander in 1981. The basic idea is to first set an initial particle as a seed, at any position away the seeds randomly generated a particle to make it random walk until the contact with the seeds, as part of the group. And then randomly generate a particle, repeat the process, so you can get enough large DLA clusters.)

联合对角化方法,用于对多个矩阵同时进行联合对角化,主要用处是盲源分离,(Joint diagonalization method, is used to conduct joint diagonalization matrix at the same time for multiple, main use is to blind source separation,)