matlab-power-system-simulation

信号与信息处理——阵列信号处理DOA估计的matlab算法，这是线性调频信号的稀疏分解算法，wigner_will分布(Signal and information processing- array signal processing matlab algorithm for DOA estimation, which is a linear FM signal sparse decomposition algorithm, wigner_will distribution)

3D Radon and its inverse

this program will help you to perform LDA and PCA signal processing tools for classifing

optimization techniques (line search, conjugate gradient)

matlab的基础教学，对于从来没有学习过matlab的同学，该文档可以提供由浅入深的详细介绍与说明。(matlab basis for teaching, never studied matlab for students, the document provides a detailed description and explanation progressive approach.)

环境下构建一种新的系统辨识仿真工具箱(SIST: System Identification Toolbox)的原理与实现,讨论了在MATLAB 环境下工具箱的数据和算法结构形式,以及利用GUIDE完成图行界面的设计,用MATLAB 与C++混编技术实现物理系统的I/O 接口和系统辨识... (err)

1/f噪声采用多分辨分析进行参数提取，并波形恢复(1/f noise analysis using multi-resolution parameter extraction and waveform recovery)

这是永磁同步直线电机的空间矢量控制模型，已经通过仿真请放心下载(This is the space vector control of permanent magnet synchronous linear motor model, the simulation has been downloaded, please be assured)

说明：  用于模拟光纤中的非线性薛定谔方程，包含了色散、非线性等现象的模拟，对与想了解脉冲在光纤中的传输变化非常有帮助(Used to simulate the optical fiber in the nonlinear Schr&ouml dinger equation, including the dispersion, nonlinear phenomena such as analog, pulse on and want to understand changes in the transmission fiber is very helpful)

去噪处理是图像处理中较为重要的环节。中值滤波是抑制图像的噪声的一个行之有效的办法，选择适当大小的中值滤波窗口可以在最大限度的保持图像精度的基础上去除图像噪声。本文在对中值滤波去噪算法的适用性特点进行研究的基础上，进一步研究了中值滤波去噪算法，同时对其他去噪算法，如均值滤波、低通滤波的小波变换进行分析研究，并做了相应的比较。(Noise reduction is one of the most important parts of image processing. Median filtering is a proven way to remove image noise. To select the appropriate size of the window can maximize to remove image noise on the basis of maintaining the accuracy of the image. On the basis of investigating the application of the median filtering algorithm denoising characteristics, we do further study of the median filtering algorithm denoising. At the mean time we analyzed the mean filtering and wavelet transform algorithm, and compared them.)