snake

详细介绍了多抽样率信号处理的原理，便于更深入了解抽取和内插滤波器的实现(Detailed introduction of multi-sampling rate of signal processing theory, to facilitate a better understanding of extraction and interpolation filters realize)

主分量分析，用于对脑电信号的判别分析，也可用于其他的二分类分析。(the classifier of principle component analysis,using for EEG and binary classification)

这篇经典文章Exact Matrix Completion via Convex Optimization的源代码(This classic article Exact Matrix Completion via Convex Optimization of the source code)

说明：  uwb各种程序，可以产生信号、冲激响应等等各类仿真任务完美完成(UWB programs can generate signals, impulse response and other simulation tasks to complete perfectly)

Pattern recognition using matlab software had a very good simulation, the use of Bayesian Classifiers for boys and girls had a very good classification.

采用映射法降低ofdm系统分均比的matlab仿真程序(Ofdm systems using sub-mapping method to reduce the matlab simulation program than)

KSVDBox - Implementation of the K-SVD and K-SVD denoise algorithms.(K-SVD dictionary training. ksvd - K-SVD dictionary training. Signal denoising. ompdenoise - OMP denoising. ompdenoise1 - OMP denoising of 1-D signals. ompdenoise2 - OMP denoising of 2-D signals. ompdenoise3 - OMP denoising of 3-D signals. ksvddenoise - K-SVD denoising. Overcomplete DCT dictionary. odctdict - Overcomplete DCT dictionary. odct2dict - 2-D overcomplete DCT dictionary. odct3dict - 3-D overcomplete DCT dictionary. odctndict - Multi-dimensional overcomplete DCT dictionary. Demonstrations. ksvddemo - K-SVD training demonstration. ksvddenoisedemo- K-SVD denoising demonstration. Miscellaneous. showdict - Display a dictionary of image patches. ksvdver - K-SVD toolbox version information.)

This is code simulates maximal ratio combining

本代码给出了一个不敏卡尔曼滤波实例和不敏卡尔曼滤波算法代码(This code gives an Unscented Kalman filter instance and not Unscented Kalman filter algorithm code)

说明：  标准粒子群算法的实现思想基本按照粒子群算法(2)----标准的粒子群算法的讲述实现。主要分为3个函数。第一个函数为粒子群初始化函数(His thought of the implementation of the standard particle swarm algorithm according to the particle swarm algorithm (2)- the standard particle swarm algorithm about implementation. Mainly divided into three functions. The first function of particle swarm initialization function)