MouseDraw_matlab

RSS测距定位模型的Cramer_Rao界分析(RSS Ranging Positioning Model Cramer_Rao sector analysis)

SCPI_99 doc. SCPI driver develp doc.entry-level to deep level, comprehensive separately.

说明：  视频帧序列实现基于GMM（高斯混合模型）的背景建模(Video frame sequence implementation based on GMM (Gauss mixture model) background modeling)

用matlab仿真随机信号白噪声，频谱分析，很好用(Matlab simulation of random signal with white noise)

使用matlab软件编程，进行字母识别处理(using Matlab software programming, in alphabetical identification processing)

Extended kalman filter for tracking

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)

说明：  广义相关法，加权函数为ML（最大似然）形式的matlab程序源代码(The Generalized Correlation Method，The weight function is ML )

ecma-368 ultra wide band ber test3

这是一个关于模态参数识别的资料，里面有几种关于模态参数识别的方法。(This is a modal parameter identification information, which there are several on the modal parameter identification method.)