histmatching

使用k-means算法对样本空间中的未分类的点进行聚类。(K-means algorithm using the sample space clustering unclassified points.)

该教程MATLAB实用教程（7.0版本）包括MATLAB语言基础、基本应用、高级应用三部分，系统全面。(The Practical Guide Tutorial MATLAB (version 7.0) includes the basic MATLAB language, basic applications, advanced applications of three parts, systematic and comprehensive.)

Hamming code BER with DPSK

本光盘为《详解MATLAB快速入门与应用》一书的配套光盘，包括以下内容： 1.“sample”文件夹：提供了本书各章范例的源程序。(The CD is " Getting Started with MATLAB Detailed application," a book supporting the CD, including the following:. 1 " sample" folder: each chapter provides examples of the book source.)

用s函数写得二级倒立摆模型，用状态反馈、最优控制、模糊控制进行仿真。(S function written with double inverted pendulum model, using state feedback, optimal control, fuzzy control simulation.)

MATLAB中ODE算法的完整例程，可以参照学习，并且可以直接改动参数，可以运行成功。(Complete routine in MATLAB ODE algorithm can refer to learn, and you can directly change the parameters, you can run successfully.)

采用L-M优化算法用以训练BP神经网络，使其能够拟合某一附加有白噪声的正弦样本数据。设计一个三层BP神经网络，其网络的隐含层神经元的激励函数为双曲正切型，输出层各神经元的激励函数为线性函数，隐含层有6个神经元(LM optimization algorithm used to train BP neural network to enable it to fit a white noise, sine additional sample data. Design a three BP neural network, its network of hidden layer neuron activation function of hyperbolic tangent type for the output layer activation function of each neuron is a linear function of the hidden layer has 6 neurons)

该源码使用主成分分析对原数据点进行分析。(Reshape the data points using the principal component analysis)

对某一标准图像进行二维Mallat小波的3级分解，获得小波高/低频系数，分别 用低频分量LL1、LL2、LL3的小波系数进行图像重建，分别计算这三种情况 和原始图像比较的PSNR。(A standard image 3 2D Mallat wavelet decomposition, wavelet high/low frequency coefficients , respectively Low frequency component LL1 , LL2, LL3 wavelet coefficients for image reconstruction, respectively, to calculate the three And compared to the original image PSNR. )

HMC5883磁力计使用前必须进行校准，这个matlab程序用来拟合磁力计的数值，然后得出补偿值(HMC5883 magnetometer must be calibrated before use, the procedure used to fit the numerical matlab magnetometer, and then come to the compensation value)