2006316144055

第7章 数值微分.zip。是从书中光盘里拷贝的代码，放在这里与大家共享，希望对大家有帮助。(Chapter 7, numerical differentiation.zip)

DYNAMIC MODELING AND CONTROL OF NONHOLONOMIC WHEELED MOBILE ROBOT SUBJECTED TO WHEEL SLIP

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)

四阶龙格库塔法解常微分方程组 四阶龙格库塔法解常微分方程组(4-Runge-Kutta)

运用shancen格子玻尔兹曼模型模拟两相分离，验证可行(Use shancen lattice Boltzmann model to simulate two-phase separation, verification feasible)

image fusion matlab code for medical application in identification of tumor

viterbi译码的快速实现算法，非常适合初学者迅速上手(Fast viterbi decoding algorithm is very suitable for beginners to get started quickly)

matlab 教程(matlab tutorial)

说明：  add noise to image and remove it with median, weiner and linear filter

dsb仿真，没有高斯白噪声的，可用！！！(dsb simulation, there is no white Gaussian noise can be used! ! !)