Proyecto_Radio_Multiplexacion_FDM_AM

对比粒子群算法中不同的权重因子C1C2对算法收敛的影响(different C1、C2 to particle swarm optimization)

A library for DW-MRI Processingg

基于MATLAB的电力系统继电保护仿真研究(MATLAB-based power system relay protection simulation study)

This is About MVDR beamforming techniques which matlab codes

This tutorial is designed to give the reader an understanding of Principal Components Analysis (PCA). PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding patterns in data of high dimension. Before getting to a description of PCA, this tutorial first introduces mathematical concepts that will be used in PCA. It covers standard deviation, covariance, eigenvectors and eigenvalues. This background knowledge is meant to make the PCA section very straightforward, but can be skipped if the concepts are already familiar.

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ACTIVE CONTOUR LEVEL SET METHOD

说明：  k-means聚类以及比较，对比比较经典的算法，读者可以自行修改等等(Clustering and comparison, comparison more classical algorithm, the reader can modify and so on)

PCA with K-nn classifier(for pictures)

卡尔曼滤波基础和实践一书的matlab源码(Fundamentals of Kalman Filtering—A Practical Approach)