hw3A

LDPC码的PEG构造,用matlab编写，希望对大家有所帮助。(The LDPC code PEG constructed matlab write, we want to help.)

bmatch.rar文件用来解决b-mathcing问题(To solve the problem of b-matching)

本科工程力学专业课程设计，有输入输出界面，程序美观大方，程序功能如下： 1.空间桁架计算的计算机程序,考虑温度变化，支座位移） 2.平面刚架计算的计算机程序( 考虑温度变化，支座位移) 3.空间刚架计算的计算机程序 4.薄板弯曲计算的计算机程序 (matlab for mechnics major)

SIMULINK很好的参考教程,给出了SIMULINK使用方法和例程,是初学者很好的参考资料(SIMULINK good information and guidance, given the use of methods and routines SIMULINK is a good reference for beginners)

这是一个Knn分类算法的Python实现，Matlab中有类似的函数(knn classifer)

基于Matlab的MIMO通信系统仿真”，收获良多，特将其记录下来，与诸位分享。此主题分为上下两部分，第一部分主要涉及系统架构，第二部分侧重程序优化。若能帮助读者一二，实属万幸。(Multi-input multi-output (MIMO) communication system based on Matlab simulation ", so, will its record, share with you. This topic is divided into two parts, the first part mainly involves the system architecture, the second part focuses on process optimization. If can help readers just a little, is lucky.)

说明：  MATLAB 有哪些主要功能? 初学者应如何利用这一数学软件去解决自己的 问题？要解决这些问题，应该尽快熟悉一些常用命令，了解它们的功能和使用 格式。(What are the main functions of MATLAB? Beginners how to use the mathematical software to solve their own problems? To solve these problems, should be familiar with some commonly used command as soon as possible, understand their function and use format.)

基于matlab的海洋通信的基础猜想，采用数字调制，2径仿真，其中损耗采用HUAWEI早年实测模型(Based on the basis of conjecture matlab marine communications, digital modulation, two-path simulation, in which the loss measured using early model HUAWEI)

说明：  遗传算法是计算数学中用于解决最佳化的搜索算法，是进化算法的一种。进化算法最初是借鉴了进化生物学中的一些现象而发展起来的，这些现象包括遗传、突变、自然选择以及杂交等。遗传算法通常实现方式为一种计算机模拟。对于一个最优化问题，一定数量的候选解（称为个体）的抽象表示（称为染色体）的种群向更好的解进化。传统上，解用二进制表示（即0和1的串），但也可以用其他表示方法。进化从完全随机个体的种群开始，之后一代一代发生。在每一代中，整个种群的适应度被评价，从当前种群中随机地选择多个个体（基于它们的适应度），通过自然选择和突变产生新的生命种群，该种群在算法的下一次迭代中成为当前种群。(Genetic algorithm (GA) is a search algorithm used to solve optimization in computational mathematics. It is one of evolutionary algorithms. Evolutionary algorithms were originally developed by borrowing phenomena in evolutionary biology, such as heredity, mutation, natural selection and hybridization. Genetic algorithms are usually implemented as a computer simulation. For an optimization problem, an abstract representation of a certain number of candidate solutions (called individuals) (called chromosomes) evolves towards a better solution. Traditionally, solutions are represented in binary (that is, strings of zeros and ones), but other representations are possible. Evolution begins with a population of completely random individuals, and it happens from generation to generation.)

Genetic Algorithm & Direct Search using Matlab.pdf