bpsk

采用MATLAB仿真BPSK-OFDM的BER特性。从理论和实际两方面把输出波形作为对比。(Using MATLAB simulation of BER of BPSK-OFDM characteristics. From both theoretical and practical aspects of the output waveform as a contrast.)

LMS算法的matlab仿真，自适应滤波器的仿真实现，很基础也很常用的方法，一定要掌握的(LMS algorithm matlab simulation, Simulation of adaptive filter, it is also the basis of common methods, we must grasp)

Adaboost是一种迭代算法，其核心思想是针对同一个训练集训练不同的分类器(弱分类器)，然后把这些弱分类器集合起来，构成一个更强的最终分类器（强分类器）。 load clouds [test_targets, E] = lijsada_boost(patterns, targets, patterns, 100, Stumps ,[]) train_patterns 每列为一样本 train_targets 每列为一样本目标 100 :Number Of Iterations Stumps: Weak Learner Type Learner s parameters :[] adaboost +stumps testRightR = 0.7522(Adaboost is an iterative algorithm)

一列火车要将n节车厢分别送往n个车站车站按1~n的次序编号，火车按照n, n-1,…, 1的编号次序经过车站。假设车厢的编号就是其目的地车站的编号。 (A train to n cars n stations were sent to stations by 1 ~ n the order of numbers, the train in accordance with n, n-1, ..., 1 after the station number sequence. Suppose car number is its destination station number.)

source code for watermark

粒子群算法OptSwarm记录每个粒子的历史最优解（粒子历史最好的适应度）以及全部粒子搜索到的全局最优解。用Wg代表全局最优解，W.,1代表每个粒子的历史最优解。粒子群初始化阶段表OptSwarm的前N行与表ParSwarm中的相同，而Wg的值为表ParSwarm中适应度值的最大值对应的行。(Particle swarm algorithm OptSwarm record the history of each particle the optimal solution (particles history best fitness), and all the particles of the search to the global optimal solution. Use Wg represents the global optimal solution, w., 1 representative of each particle history to the solution. Particle swarm initial stage OptSwarm table before the line and the table ParSwarm N is same, and the value of the ParSwarm Wg for tables in the maximum fitness value corresponding line. )

曹梦龙 仿真大实验 实验四包括所有有用数据(Caomeng Long simulation experiment in Experiment 4, including all useful data)

matlab 100个小程序，可以好好看看，都是经典的学习各种知识应用(matlab knowledge)

simulink for Low-density parity-check code

install code to the document,and replease ,make project