MATLAB_animation

两个简单序列的褶积，是地球物理信号处理的简单基本程序(convolution of two alignments)

MATLAB分布式电力系统状态估计完整程序.用于分布式光伏电站并网(MATLAB distributed power system state estimation complete program for distributed photovoltaic power station grid connected)

基于MATLAB仿真的智能BP算法集合，用于先进控制理论的研究，主要是控制器方面的介绍(BP algorithm based on MATLAB simulation smart collection for the study of advanced control theory, mainly the introduction of the controller)

this mi test m-file for matlab program

说明：  ：Mean—shift算法是一种非参数密度估计算法，可以实现快速的最优匹配，在目标的实时跟踪领域起着非常 重要的作用。为了有效的将Mean—shift算法应用到灰度图像中，采用了以方向直方图建立目标模型的策略，提出了在灰 度图像中以Mean—shift为核心的目标跟踪算法。实验结果表明，该算法具有不受光照条件影响的优点，在低对比度的情 况下仍能实现稳定、实时的跟踪目标。(: Mean-shift algorithm is a nonparametric density estimation algorithm, the optimal matching can be fast, real-time tracking fields in the target plays an important role. In order to effectively Mean-shift algorithm will be applied to the gray image, the histogram used to establish the direction of the strategy target model is proposed in the gray image to Mean-shift tracking algorithm as the core. Experimental results show that the algorithm has the advantage of not lighting conditions, in the case of low contrast can still achieve stability, real-time tracking of targets.)

模拟战斗机平显画面，实现ccrp投弹方式，速度高度表可动态显示(HUD screen fighter simulation to achieve ccrp bomb mode, speed altimeter dynamic display)

APMTMLHDGV01Ver2001_Tools_Software_general_05011YXC.rar华为手机刷机平台(Tools Software general )

Reinforcement Learning 中以 Q learning 學習的倒單擺實驗。以x,x_dot,theta,theta_dot作為狀態參數 state，利用model模擬之結果做Q值更新，產生Q table，對學習平衡控制。結果以csv檔作為輸出，可以由使用者作圖觀察變化。(Reinforcement Learning , utilize Q learning for An inverted pendulum system control。x,x_dot,theta,theta_dot as state variable，use model result renew Q table，control learning of balance pole 。output csv file contain trail(times),balance time(sec).it s better observe the change if user plot it. )

Kinetis KL26 low power mode example, wake up by TSI interrupt. CW 10.x project

old videoplayers src :cinemaplayer,subedit,viplay+the scientist & engineer s guide to digital signal processing.pdf(full)