mlclass-ex1

这是一个相关系数分析的算法代码，用matlab编写的(This is a correlation coefficient analysis of the algorithm code, prepared by matlab)

说明：  这个是关于neural fuzzy 算法的工具箱, 有例子程序, 请您用winzip解压缩(is on the neural fuzzy algorithm toolbox, there are examples of procedures, please use winzip decompress)

说明：  电压型逆变器供电永磁同步电动机传动系统的动态仿真(The voltage type inverter power supply of permanent magnet synchronous motor drive system dynamic simulation)

人工智能算法，蚁群算法，人工免疫算法等matlab程序(Artificial intelligence algorithms, ant colony algorithm, artificial immune algorithm matlab program)

基于扩展卡尔曼滤波的slam仿真，使用matlab，有路标点和运动轨迹，仿真真实环境(This is a Extended Kalman Filter based SLAM example)

ofdm正交频分复用系统误码率ber，比较简单，基础框架(the ber of ofdm system)

2D FFT and 2D IFFT in matlab. inputs are original data and block size. ex) block size = [8 8]

说明：  实验一：基于LMS算法的“苹果-橘子”分类问题 实验二：基于LMS算法的T-G-F字符识别问题 通过以上两个实验，了解ADALINE网络的结构及计算机制，掌握LMS算法，并会利用该算法来解决简单的模式分类问题。1， 学习ADALINE网络的基本结构及其学习机制，并在Matlab中实现 2， 分别对上述两类分类问题进行实现，并根据实验结果完成实验报告 (Experiment 1: Based on LMS Algorithm Apple- Orange classification issues Experiment two: TGF-based character recognition problem LMS algorithm Through the above two experiments to understand the structure and computer network system ADALINE, master LMS algorithm, and will use the algorithms to solve simple pattern classification problem. 1, learn the basic structure and learning mechanism ADALINE network and to achieve in Matlab 2, respectively, for these two types of classification problems were implemented and completed in accordance with the experimental results of test report)

对噪声信号中的正弦信号，通过Pisarenko谐波分解方法、Music算法和Esprit算法进行频率估计，信号源是： 其中， ， ， ； 是高斯白噪声，方差为 。使用128个数据样本进行估计。 1、用三种算法进行频率估计，独立运行20次，记录各个方法的估计值，计算均值和方差； 2、增加噪声功率，观察和分析各种方法的性能。(Sinusoidal signal in the noise signal through the Pisarenko harmonic decomposition method, Music algorithms and Esprit frequency estimation algorithm, the signal source is: where,,, a Gaussian white noise, variance. 128 data samples used to estimate. 1, with three kinds of frequency estimation algorithm, run independently 20 times, record the estimated value of each method to calculate the mean and variance 2, the increase in noise power, observation and analysis of the performance of various methods.)

Active approach - TOA LS(Active approach- TOA LS)