cosine

QC_LDPC 编译码的程序和扩频序列的程序，希望对大家有用(QC_LDPC coding and decoding process and the spreading sequence of procedures in the hope that useful)

使用matlab工具完成mcmc（马尔科夫蒙托卡罗）方法的计算。包含多个m文件。(Matlab tools to complete the MCMCcalculations. Contains more than one m file.)

这是我们通信建模与仿真书上的程序，是白噪声＆瑞利信道下对OFDM的仿真实现。(This is our communication on Modeling and Simulation on the procedures, White Noise & Rayleigh Channel on OFDM Simulation.)

轮胎力学特性，魔术公式，包含多个工况，可以修改参数，m文件(Tire mechanical characteristics, magic formula, contains more than one condition, you can modify the parameters, m file)

本资源中包含了在matlab环境中常用的基本算法程序，其中也有大量的例子进行说明。(This resource contains the environment in matlab basic algorithm commonly used procedures, which also has a large number of examples will be described.)

说明：  用于声发射信号参数分析的GUI平台，基于excel格式文件(The GUI platform for acoustic emission signal parameter analysis is based on Excel format file)

PMCH信道仿真，需要的朋友可以参考一下啊(PMCH channel simulation, the needs of friends can make reference to it)

1．本程序演示的是用简单遗传算法随机一个种群，然后根据所给的交叉率，变异率，世代数计算最大适应度所在的代数 2．演示程序以用户和计算机的对话方式执行，即在计算机终端上显示“提示信息”之后，由用户在键盘上输入演示程序中规定的命令；相应的输入数据和运算结果显示在其后。 3．测试数据 输入初始变量后用y=100*(x1*x1-x2)*(x1*x2-x2)+(1-x1)*(1-x1)其中-2.048<=x1,x2<=2.048作适应度函数求最大适应度即为函数的最大值 (1. This program demonstrates a simple genetic algorithm is a random population, then according to the crossover rate and mutation rate, fitness for calculating the maximum number of generations in which algebra 2. Demo program to computer users and the implementation of dialogue, that is displayed on a computer terminal " message" after the keyboard input by the user specified in the order demo program the corresponding input data and results in a subsequent operation. 3. Test data input with the initial variables y = 100* (x1* x1-x2)* (x1* x2-x2)+ (1-x1)* (1-x1) where-2.048 < = x1, x2 < = 2.048 ask for the maximum fitness function is the function of the maximum fitness)

使用matlab中simulink仿真电机控制的初学者，可以看看(Matlab motor control simulation for beginners, you can download a look)

Locally linear embedding(LLE)是一个经典的流形学习降维方法，通过LLE发现高维数据潜在的内在维数，可以简化计算、方便可视化处理等。(Locally linear embedding (LLE) is a classic manifold learning dimensionality reduction method, discovered by LLE potential inherent high dimensional data dimension, the calculation can be simplified to facilitate visual processing.)