GUIDEvideo2

这是一个rbf神经网络建模的MATLAB源程序(This is an rbf neural network modeling of the MATLAB source code)

压缩传感置信传播算法的matlab仿真全部源程序。信号模式为二值高斯信号，编码测量采用类似LDPC矩阵。(Belief propagation algorithm for compressed sensing all the source code matlab simulation. Gaussian signal model for binary signals, LDPC coding was measured using a similar matrix.)

国外的一篇文章，首次介绍压缩粒子滤波方法及其在目标跟踪中的应用(Foreign article first introduces compressed particle filter method and its application in Target Tracking)

This is Newton-Raphson program matlab to calculat load flow of electrical grid

This code computes the distance and azimuth an earthquake to a station. It is necessary to provide the latitude and longitude bothe for the earthquake and the station.

说明：  nmf盲源分离，使用欠定的方法，可以用来分离两路语音信号，人声与其他音的分离(nmf_bss.The underdetermined method can be used to separate two voice signals, human voice and other voices.)

本程序为实值空间ESPRIT算法源程序，是基本ESPRIT算法在性能上的一种改进(This program is in real space ESPRIT algorithm source code, is a basic algorithm ESPRIT an improvement in performance)

this is a matlab program which implement cmt algorithm for detection objects in signals

在一个移动通信系统中，发射信号是一个未调制的音频x(t)=cos(2πft)，其中f=f0+fi。设标称载波为f0=1GHz，并设fi =512Hz。假定移动用户在一个繁忙的高速公路上距离基站l公里处的地方，从开始从每小时60公里的速度开始，其速度（在0.01秒的时间间隔内测量）以1/2的概率随机的增加或减少1/10公里每小时。试仿真移动用户在这2s的时间间隔内所接收到的信号(及其频谱)。接收信号可以表示为： y(t)=a(t)Cos[2π(fo+f1)(t-△t)] 式中 △(t)=d(t)/c 且 a(t)=k/d2(t) 在上面的表达式中d(t)是在t时刻基站与移动用户的距离，c是光速，△(t)是传播延迟，而a(t)是信号在t时刻的衰减，并假设在这2s内a(t)是一个常数。利用复低通等效模型来进行仿真。(In a mobile communication system, the transmitted signal is an unmodulated audio x (t) = cos (2πft), where f = f0+ fi. Let nominal carrier of f0 = 1GHz, and set fi = 512Hz. Assume that mobile users on a busy motorway station l kilometers place, starting the beginning of 60 kilometers per hour, the speed (measured in 0.01 second interval) to increase the probability of a random 1/2 or reducing 1/10 km/h. Simulation test signal which the mobile subscriber in the 2s time intervals of the received (and its spectrum). The received signal can be expressed as: y (t) = a (t) Cos [2π (fo+ f1) (t- △ t)] Where △ (t) = d (t)/c And a (t) = k/d2 (t) In the above expression, d (t) at time t is a base station and a mobile user s distance, c is the speed of light, △ (t) is the propagation delay, and a (t) is the attenuation of the signal at time t, and assuming that 2s within a (t) is a constant. Using complex low-pass equivalent model for emulation.)

system analysis theory and methodology