pulse_shaping_filter

without dstatcom. here non linear load and star connected loads are used to generate the harmonics

一种（LFM）Linear frequency modulation雷达的仿真(Linear frequency modulation (LFM) radar simulation)

说明：  用矩阵实现而微小波变换，解决途中处理中而微信息量过大的问题(Realization with small wave transformation matrix to address the way in which micro-processing problem of information overload)

matlab应用于基于粒子滤波的程序及演示(Particle filter based on the procedures and presentation of matlab)

联合开发网 - pudn.com

MATLAB中simulink环境下S函数编写的教程(MATLAB simulink environment in the S function written tutorial)

关于无线通信用matlab中的simulink模块仿真的例子，很实用，特适合初学者(Example of the simulation of wireless communication matlab simulink module is very useful, especially for beginners)

相当好的matlab数字图像处理，包括基本原理、图像复原、彩色处理、图像压缩、分割(Very good matlab digital image processing, including the basic principles, image restoration, color processing, image compression, segmentation)

LTE performance thesis

In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets. (In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar-xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets. )