Gaussn_Clutter

AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files 1. ADABOOST_tr.m 2. ADABOOST_te.m to traing and test a user-coded learning (classification) algorithm with AdaBoost. A demo file (demo.m) is provided that demonstrates how these two files can be used with a classifier (basic threshold classifier) for two class classification problem.(AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files 1. ADABOOST_tr.m 2. ADABOOST_te.m to traing and test a user-coded learning (classification) algorithm with AdaBoost. A demo file (demo.m) is provided that demonstrates how these two files can be used with a classifier (basic threshold classifier) for two class classification problem.)

说明：  利用NSGAII算法进行对复杂网络的社区检测(community detection in complex network)

了解粒子群算法的功能，怎么用matlab来编写粒子群算法(Understand the functions of particle swarm optimization, how to write using particle swarm optimization matlab)

LTE模型 LTE模型 LTE模型 LTE模型(LTE LTE model model model LTE LTE model)

In computer science and information theory, data compression, source coding,[1] or bit-rate reduction involves encoding information using fewer bits than the original representation. Compression can be either be lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by identifying marginally important information and removing it. The process of reducing the size of a data file is popularly referred to as data compression, although its formal name is source coding (coding done at the source of the data, before it is stored or transmitted).

Very low cost, low component count charger/adapter – replaces linear transformer based solutions • Extremely simple circuit configuration designed for high volume, low cost manufacturing

成本低,制作简单的TV视波器，有图，说明。(Low cost, make a simple TV as the wave device, with diagrams, instructions.)

该程序可实现多个图像的线性分离，假设在无噪声情况下，运用多种方法实现分离。(the procedure can be more than a linear image separation, assuming no noise, using various methods to achieve separation.)

Lagrange Interpolation

模拟退火程序，用MATLAB语言实现，并带有程序算法说明(simulated annealing)