PQ

说明：  实现ASK、FSK、PSK数字调制系统的仿真，观察功率谱密度，眼图，对系统的仿真误码率与理论误码率进行比较(Realize the simulation of ASK digital modulation system, observe the power spectral density and eye diagram, and compare the simulation error rate with the theoretical error rate of the system.)

DSPtms6417+ARM9的一个亮灯小程序，主要有参考意义，可以在omapl138上面跑，在ccs上面打开。需要加载syslink(DSPtms6417+ ARM9 of lighting a small program, the main reference value, can be run in omapl138 above, the top can be opened in ccs. Need to load syslink)

说明：  在E.C.Levy的“光电振荡器建模”一文中，利用MATLAB函数编写了单回路OEO仿真程序。为了说明它的用途，我们生成图2，4，5，8和11。(The single-loop OEO simulation is written by using MATLAB functions)

空域滤波代码，对阵列信号处理，滤除不需要方向上的信号(Spatial filtering code, array signal processing, filtering do not need direction signal)

Algoritmos pra reconhecimento facial

低压svg仿真，验证通过，确定可以运行。(Low Voltage Reactive Power Compensation Simulation)

TMS320C5509A上实现IIR滤波器算法(TMS320C5509A achieve IIR Filter Algorithm)

说明：  NOMA系统级仿真，多用户，多径瑞利信道(NOMA System Level Simulation)

说明：  TMS320F28335串口接收发送数据(TMS320F28335 serial port sending and receiving program)

一个比例和方向自适应均值漂移跟踪算法（SOAMST） 提出本文所要解决的问题，如何估计的规模和方向 改变均值漂移下的目标跟踪框架。在原来的均值偏移 跟踪算法，可以很好地估计目标的位置，规模的同时， 方向的变化，不能自适应估计。考虑到图像（重量） 是来自于目标运动模型和候选模型可以代表的可能性，一个 像素属于目标，我们证明了原来的均值漂移跟踪算法可以 推导出的重量图像的零阶和一阶矩。随着零阶 矩和目标模型和候选模型之间的Bhattacharyya系数， 提出了简单而有效的方法来估计的规模为目标。然后一种方法， 利用估计的区域和第二阶中心矩，提出 自适应地估计目标的宽度，高度和方向的变化。广泛 实验来证实所提出的方法，并验证其可靠性 规模和方向变化的目标。(A scale and orientation adaptive mean shift tracking (SOAMST) algorithm is proposed in this paper to address the problem of how to estimate the scale and orientation changes of the target under the mean shift tracking framework. In the original mean shift tracking algorithm, the position of the target can be well estimated, while the scale and orientation changes can not be adaptively estimated. Considering that the weight image derived from the target model and the candidate model can represent the possibility that a pixel belongs to the target, we show that the original mean shift tracking algorithm can be derived using the zeroth and the first order moments of the weight image. With the zeroth order moment and the Bhattacharyya coefficient between the target model and candidate model, a simple and effective method is proposed to estimate the scale of target. Then an approach, which utilizes the estimated area and the second order center moment, is proposed to adaptively e)