difference-and-fitting-simulation

暂态稳定计算，计算在短路和断路情况下系统的状态量(Transient stability)

说明：  雷达目标航迹跟踪，运行函数main_test，进行雷达数据处理，最终显示航迹；(Radar Target Tracking，Run the function main_test, the radar data processing, the final display track )

说明：  运用Matlab求解三个传递函数的群延迟特性曲线(Use Matlab to solve the three transfer function of the group delay characteristic curve)

程序仿真得图为原信号与u律压扩信号的互补累积函数曲线图。仿真参数：子载波N=128，采用QPSK调制。(The photo shows the original simulation program was u-law signal and the signal of the complementary cumulative function expansion curve. Simulation parameters: sub-carriers N = 128, using QPSK modulation.)

BP神经网络对2ask,2fsk,4fsk,2psk,4psk,gmsk六种信号的学习和训练。 (BP neural network 2ask, 2fsk, 4fsk, 2psk, 4psk. gmsk six signals in the learning and training.)

MATLAB图形技术——绘图及图形用户接口(MATLAB graphics- graphics and graphical user interfaces)

matlab 小波变换 有嵌入水印部分和提取水印部分(watermarking)

ESPRIT是“Estimating signal parameters viarotational invariance techniques”的缩写，含义是“借助旋转不变技术估计信号参数”，它是由Roy[221等人于1986年提出的另一种基于子空间的DOA估计方法。 应用领域 　　侧向定位 信号处理 思想 　　ESPRIT的思想在于，将传感器阵列分解为两个完全相同的子阵列，两个子阵中每两个相对应的阵元具有相同的平移，即要求阵列具有平移不变性，每两个位移相同的阵元匹配成对。所幸的是实际中许多阵列满足这个条件，比如等距直线阵。(ESPRIT is "Estimating signal parameters viarotational invariance techniques" acronym, meaning "With ESPRIT estimation of signal parameters", it is by Roy [221, who in 1986 proposed DOA estimation method based on subspace another. Applications Lateral positioning signal processing Thinking ESPRIT thinking that the sensor array is divided into two identical sub-arrays, each of the two sub-arrays of two corresponding array element has the same translation, which requires an array with translation invariance, the displacement of each of the two identical arrays yuan matching pairs. Fortunately, many of the actual array satisfy this condition, such as equidistant linear array.)

基于最小二乘支持向量机对传感器的非线性系统用MATLAB软件进行仿真建模程序(Based on least square support vector machine (SVM) of the nonlinear system of sensor with MATLAB simulation modeling software program)

comparative analysis of random forest with different feature selection algorithms.