DOA估计

说明：  这个文件是QPSK的编码文件，利用的是matlab的开发环境，实用的小程序(This file is QPSK encoded file, using the matlab development environment, a small utility program )

说明：  对视频序列通过背景减除法进行运动跟踪，里面用到的方法是叠代法(Motion tracking video sequences by background subtraction)

实现qpsk调制，通过瑞丽信道和高斯信道 然后计算其误码率 并进行比较(Qpsk modulation to achieve, by Rui Lixin Road and Gaussian channel and then calculate the error rate and compare)

多功能信号分析器.基于matla的GUI界面.实现对信号的波形频谱显示。且包括对加窗以后数据的峰值相应坐标的捕获. (Multifunctional signal analyzer. Based MATLA the GUI interface. Displayed on the waveform of the signal spectrum. And including the capture of the windowed data after the peak corresponding coordinates.)

多工序多设备的生产车间调度问题，采用的是精英保留策略的遗传算法(A genetic algorithm based on elite reservation strategy is adopted for multi-process and multi-equipment job shop scheduling problem.)

对蓄电池采用低压配电网 P/V 和 Q/f 下垂控制策略 ， 实现从并网运行到孤岛模式的切 换 。 考虑实际风速和光照强度的变化 ， 对风能与光伏混合微电网在并网和孤岛 2 种模式中的运行特性进行 仿真分析 ， 验证控制方式的可行性(The realization of the operation the grid to the island change . Considering the actual wind speed and light intensity , Hybrid grid for wind energy and photovoltaic grid connected and isolated Two The operating characteristics of the Simulation analysis , Verify the feasibility of control mode)

采用matlab模型，采用三维纹理绘制的方式，绘制三维模型(Matlab model by using three-dimensional texture drawing method, draw the three-dimensional model)

说明：  calculator using matlab

该资料为机器人学的实验材料，包括仿真软件，实验题目以及实验解答(The data for the robotics experiment materials, including simulation software, test questions and test answers)

MUSIC算法[1]是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成。(MUSIC algorithm [1] is a feature space based on matrix decomposition method. From the geometric point of view, the signal processing can be decomposed observation space the signal subspace and the noise subspace, it is clear that the two spaces are orthogonal. Signal Subspace data received by the array covariance matrix and eigenvectors corresponding to the signal component, the noise subspace from the covariance matrix of all the smallest eigenvalue (noise variance) eigenvector components.)