Digital-signal-processing

基于相量测量的输电线路故障测距新算法 关键词：相量测量；线路参数；故障测距(PMU for Transmission Line Fault Location Algorithm Key words: phase measurement line parameters fault location)

matlab 卡尔曼滤波实际例子，附带详细注释(Kalman filter matlab practical examples, with detailed notes)

灰色PID的改进，采用灰色预估补偿，实现位置跟踪(the improved grey PID , gray predictor to achieve location tracking)

Blind Sources Separation code

说明：  基础BPSO的matlab程序,可用于学习使用(Matlab program of basic BPSO)

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.)

多分辨率融合的综述文章值得一看 多分辨率融合的综述文章值得一看 (Summary of multi-resolution integration article to see a synthesis of multi-resolution fusion article worth a visit)

传统的music算法仿真 通信信号处理 功率普估计 波达方向估计 (Traditional music algorithm simulation communications signal processing power Pu estimated DOA Estimation)

為matlab的影像增強程式，屬於小專題，可以參考看看(This is a program matlab image enhancement)

OpenCV的全称是：Open Source Computer Vision Library。OpenCV是一个基于（开源）发行的跨平台计算机视觉库，可以运行在Linux、Windows和Mac OS操作系统上。它轻量级而且高效——由一系列 C 函数和少量 C++ 类构成，同时提供了Python、Ruby、MATLAB等语言的接口，实现了图像处理和计算机视觉方面的很多通用算法。(OpenCV s full name is: Open Source Computer Vision Library. OpenCV is based on (open) issued a cross-platform computer vision library, you can run on Linux, Windows and Mac OS operating systems. It is lightweight and efficient-++ class is composed of a series of C functions and a few C, while providing an interface to Python, Ruby, MATLAB and other languages​ ​ , to achieve a lot of generic algorithm for image processing and computer vision.)