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matlab教程，matlab参考书，学习matlab必备啊！(matlab for study.)

different types of convolution

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)

Eigenvalues and eigenvectors of a normal matrix A.

matlab聚类分析源代码，本程序采用的是系统聚类方法。(the programe of matlab )

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LTE 64QaM 实现，matlab算法(development of LTE 64Qam)

一种考虑观测噪声和系统噪声的滤波算法，绘制出了目标轨迹和跟踪效果、x、y轴的滤波方差、位置均方根误差和速度均方根误差。(Consider an observation noise and system noise filtering algorithm, to map out the trajectory of the target and tracking results, x, y-axis variance filtering, position and velocity RMSE root mean square error.)

Derive for the element stiffness with symbol calculation in Matlab

说明：  matlab_矩形检测代码 刚刚用过很实用。可以下载看看(matlab_ rectangular test code just used the very practical. You can download to see)