DR-CODE

recognition system for speaker identification

matlab应用的小程序 可以根据需要更改参数(matlab applications, applets can change parameters)

Debye级数展开模型计算双层球形粒子散射角——散射光强曲线： 1. RB1.m 计算第一类Ricatti-Bessel函数的函数 2．RB2.m 计算第二类Ricatti-Bessel函数的函数 3. Alegendr.m 计算角函数 和 的函数 4. MieCoeff.m 计算米尔系数的函数 5. Amp.m 计算散射光复振幅的函数 6. DebyeIntensity.m Debye级数展开模型画包覆粒子散射角-光强图 (Debye series expansion model double spherical particle scattering angle- scattering intensity curve: 1. RB1.m calculated first class Ricatti-Bessel function of the function 2. RB2.m calculate the second category Ricatti-Bessel function of the function 3. Alegendr.m computing angle functions and function 4. MieCoeff.m Mill coefficient calculation function 5. Amp.m calculate the scattering amplitude recovery function 6. DebyeIntensity.m Debye series expansion model painted coated particle scattering angle- light intensity diagram)

利用matlab封装的底层模块的三种方法( 利用matlab封装的底层模块的三种方法)

实现利用RANSAC方法对输入图像的线特征检测的功能。(RANSAC method to achieve the input image using the line feature detection function.)

matlab中的关于CDMA接收和发射的部分simulink(Simulation of CDMA Transmitter And Receiver in Matlab)

用软件实现的滤波器，基于matlab，包含源文件和项目设计的论文和报告(DF based on matlab)

最小冗余最大相关性（MRMR）（MRMR.M） 需要外部库。详情请见MRMR。下载一个更新版本的互信息工具箱 偏最小二乘（PLS）回归系数（ReGCOEF.m） 使用MATLAB统计工具箱中的PLSReress ReliefF（分类）和RReliefF（回归）（ReleFracePr.M.） 从Matlab STATS工具箱中包装Releff.m。这是Matlab R2010B以后提供的。 ReliefF的另一个选择是使用ASU特征选择工具箱中的代码。这使用WEKA工具箱的ReleFEF，因此需要额外的库。请参阅相应的文档。 费雪评分（Fisher评分） 围绕ASFS特征选择工具箱围绕FSFisher。M(Minimum Redundancy Maximum Relevance (mRMR) (mRMR.m) Needs external library. See mRMR.m for details. Download a newer version of the mutual information toolbox Partial Least Squares (PLS) regression coefficients (regCoef.m) Uses plsregress.m from MATLAB statistics toolbox ReliefF (classification) and RReliefF (regression) (relieffWrapper.m) Wraps around relieff.m from the MATLAB stats toolbox. This is available MATLAB r2010b onwards. Another option for ReliefF is to use the code from ASU Feature Selection toolbox. This uses ReliefF from weka toolbox and hence needs additional libraries. Please see the corresponding documentation. Fisher Score (fisherScore.m) Wraps around fsFisher.m from the ASU Feature Selection toolbox)

说明：  基于灰色系统的预测，内涵数列预测和较难实现的包络预测(Prediction based on gray system, meaning the number of columns predictable and difficult to achieve the envelope prediction)

在线学习矩阵分解和稀疏编码,稀疏编码是永远的经典，需要学习稀疏编码的同志可以下载看看(Online learning and sparse coding matrix decomposition, a sparse coding is eternal classic, and need to learn the comrade of sparse coding can download and see)