munkan_v83

MARKOv的应用 Step 1，求出各食品数据的增长率； Step 2，编程，使快速上升（>=0.03） ，在程序中用“2”表示；缓慢上升 (0,0.03)，在程序中用“1”表示；相对不变 0，在程序中用“0”表示；缓慢下降(-0.03,0) ，在程序中用“-1”表示；快速下降 (<=-0.03)，在程序中用“-2”表示；得到各类食品在不同时期的 ； Step 3，统计相邻增长率变化的一致的次数 ，就菜籽油而言，在2010-3-5到2011-3-15，其增长率为先快速增长后相对不变出现的次数为‘20’=1；具体42中食品的输出情况见附录； Step 4，对每一种食品，分五类进行叠加求和，分别为“先快速增长”、“先缓慢增长”、“先相对不变”、“先缓慢下降”、“先快速下降”；得到 ； Step 5，求出一步转移概率矩阵E ；即 每行的每五个数据依次与对应的 相除，得到概率矩阵E 的一行； Step 6，使用求出的一步转移概率矩阵E ，并求出不同时期的状态概率(MARKOv application Step 1, to obtain the growth rate of each food data Step 2, the programming, so fast rise (> = 0.03), in the program with " 2" slowly rising (0,0.03), used in the program " 1" indicates relatively constant 0, by the program " 0" indicates slow decline (-0.03,0), in the program by " -1" rapid decline (< =- 0.03), in the program with " -2" means get all kinds of food at different times Step 3, the same number of adjacent growth statistics change on rapeseed oil, in 2010-3-5 to 2011-3-15, Its growth rate is relatively rapid growth of the number of times after the first change occurs is ' 20' = 1 42 Output of specific food in Appendix Step 4, for each kind of food, five points are superimposed sum, respectively, " First of rapid growth," " first slow growth" , " first relatively unchanged" , " first slow down" , " first rapid decline" get Step 5, to obtain a step)

This is a complex model of a wind turbine.

bioinformatics s function pseudo inv-robot

三次样条曲线拟和，能够很好的处理离散点的拟和问题，值得收藏(Cubic spline curve fitting and)

assigning complex numbers

内点法计算3节点系统最优潮流 3节点系统(Interior point method to calculate three-node system OPF 3-node system)

车间作业调度问题Matlab源码,用于完成车间作业的最优化调度(Job Shop Scheduling Problem Matlab source code for the completion of Job Shop Scheduling Optimization)

fractal compression of fractalized image

分水岭分割的实现，主要分四个部分：1，模拟浸水过程；2，模拟降水过程；3，过度分割问题；4，标记分水岭分割算法(The realization of watershed segmentation is mainly divided into four parts: 1. 2. Simulated precipitation process; 3. Excessive segmentation; 4. Marking watershed segmentation algorithm)

用于解反问题的共轭梯度法，对于Ax=b，输入矩阵A，列向量b，以及迭代步数k，可求的列向量x(Solution of inverse problems for the conjugate gradient method, for Ax = b, the input matrix A, the column vector b, as well as the number of iterations k, rectifiable column vector x)