HOSA

说明：  K最近邻(K-Nearest Neighbor，KNN)分类算法，是一个理论上比较成熟的方法，也是最简单的机器学习算法之一。(K nearest neighbor (K-Nearest Neighbor, KNN) classification algorithm, is a more mature approach in theory is the simplest machine learning algorithms.)

地震信号处理当中应用小波去除面波干扰，小波变换后进行阈值处理，反变换之后得到面波压制后的地震信号(Surface wave seismic signals obtained after the seismic signal processing to suppress them after removing the surface wave interference wavelet, wavelet transform thresholding, anti transformed)

kalman filter在参数估计中的应用(Kalman filter to estimate the parameters of)

this is a m-file hn matlab and it exellent

face recognized with Matlab

介绍MIMO雷达的发展趋势以及发展方向，适合初学者对MIMO雷达的研究(the introduce of the MIMO radar)

MNIST手势识别数据库进行softmax回归分类，直接运行softmaxExercise.m文件即可运行。(The MNIST gesture recognition database is classified by soft Max regression and can be run directly by running the softmaxExercise. m file.)

Discrete Random Signals and Statistical Signal Processing Sol Manual-Charles W. Therrien

matlab project for vfinal year

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 InitSwarm(SwarmSize......AdaptFunc)其主要作用是初始化粒子群的粒子，并设定粒子的速度、位置在一定的范围内。本函数所采用的数据结构如下所示： 表ParSwarm记录的是粒子的位置、速度与当前的适应度值，我们用W来表示位置，用V来代表速度，用F来代表当前的适应度值。在这里我们假设粒子个数为N，每个粒子的维数为D。(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 InitSwarm (SwarmSize... AdaptFunc), its main function is to initialize particle swarm particle, and set the particle s velocity, position in a certain range. The function of data structure is as follows: ParSwarm record table is the particle s position, speed and the current fitness value, we use W to represent the position, represented speed with a V, to represent the current fitness value with F. Here we assume that the number of particles N, each particle dimension for D.)