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Road extraction by gradient density

粒子滤波一个小演示源码，比较好用，有需要的赶紧下吧-Part.rar(Particle filter a small demonstration source, relatively easy, there is a need to quickly lower right-Part.rar)

Aion Item Templates for Aion 1.9

本文介绍了两种新的图像增强算法:一种是基于模糊嫡的图像滤波器，另一种是改进的模糊松弛迭代增强算法。前者将图像分为若十窗日，分别计算每个窗日关于不同模糊集的模糊嫡，根据最 小模糊嫡原则，确定该窗日中心灰度的大小，该方法充分利用了图像窗日中像素的区域信息。 (This paper introduces two new image enhancement algorithm: one is based on fuzzy entropy image filters, another improved fuzzy relaxation iterative enhancement algorithms. The former image into the ten windows day, the date of each window on different fuzzy sets fuzzy entropy, were calculated according to the minimum fuzzy entropy principle, determine the size of the window day center gray, full use of the Japan-China pixels of the image window region information.)

在一张表中标注了CTFT，DTFT，DFT之间的对应关系，列出公式，给出了简单认证，同时加上文字说明(Marked in a table of correspondence between CTFT, DTFT, DFT between lists formula gives a simple certification, plus text)

抛物线法求解 方程的构造方法:给出[0,1]区间上的随机数(服从均匀分布)作为方程的根p*. 设你的班级数为a3,学号的后两位数分别为a2与a1,从而得到你的三次方程 例如:你的31班的12号,则你的方程是21x3+60x2+2x+a0=0的形式. 方程中的系数a0由你得到的根p*来确定.(parabolic equation method Construction Methods : given interval [0,1] on the random number (subject to uniform distribution) as the root equation p*. set up your classes at a3, after learning of the double-digit for a1 and a2, so you get the three equations for example : your 31 classes on the 12th, then your equation is 21x3 60x2 2x a0 = 0 forms. the equation coefficients a0 you get from the root of p* to determine.)

说明：  经验模式分解matlab程序，有说明易上手效果好(Empirical mode decomposition of Matlab program, there are instructions for easy-to-use and good effect)

discrete timing control system with matlab

流水线型车间作业调度问题可以描述如下：n个任务在流水线上进行m个阶段的加工，每一阶段至少有一台机器且至少有一个阶段存在多台机器，并且同一阶段上各机器的处理性能相同，在每一阶段各任务均要完成一道工序，各任务的每道工序可以在相应阶段上的任意一台机器上加工，已知任务各道工序的处理时间，要求确定所有任务的排序以及每一阶段上机器的分配情况，使得调度指标(一般求Makespan)最小。下面的源码是求解流水线型车间作业调度问题的遗传算法通用MATLAB源码，属于GreenSim团队原创作品，博客上发布的是不完全的源码，本人将其补充完成已成功运行，转载请注明GreenSim团队原创作品。(Pipelined job-shop scheduling problem can be described as follows: n tasks on the assembly line m processing stages, each stage has at least one machine and at least one stage there are multiple machines, and the same processing performance of each machine on the same stage , at every stage to complete each task are a process, each process of each task can be processed on any machine on the corresponding stage of the processing time of each process known tasks, all tasks required to determine the sort and every Distribution of the machine on a stage, making scheduling index (typically seek Makespan) Min. The following code is a Genetic Algorithm for Job Shop Scheduling Problem pipelined general MATLAB source code, original works belong GreenSim team, the blog post is incomplete source code, I will supplement has been successfully completed its operation, please indicate the original team GreenSim works.)

lowpass filters in matlab