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高斯马尔科夫
- 高斯--马尔科夫过程的matlab代码以及仿真
DSP中含有gauss白噪声的双频正弦输入
- DSP中输入信号的生成过程。 conio.cpp实现X(n)信号，其中有两个频率分量的正弦信号（正弦计算由sinwn.cpp实现），频率可变，这里取140Hz和70Hz。 考虑了高斯白噪声，由gauss.cpp实现。 最后该信号共产生2000个点，最后的信号点存储于 “x.txt”文本中。-DSP input signal generation process. Conio.cpp achieve X (n) signal, in wh
MAT_SORCOD
- 高斯过程应用与回归分析的matlab程序-Gaussian process with the application of regression analysis procedures Matlab
GussianProcess
- 高斯过程在空间统计学中的研究已有很长时间，但其在最近十年才开始应用到非线性建模中。本例为高斯过程用于回归分析的MatLab实现。-Gaussian process in the space of statistical research for a very long time. but in the last decade only applied to nonlinear modeling. The cases of Gaussia
Rayleigh_Channel
- Gauss_generator利用参数（多普勒频移、系数、相移）生成确定的实高斯过程.m gaussian确定离散多普勒频移、系数、相移的程序.m Rice_generator在瑞利过程的基础上考虑视距分量，生成莱斯过程.m Suzuki_generator成确定型Suzuki过程.m Rayleigh_Doppler_multiPath.m Rayleigh_Doppler_singlePath.m rayleigh_Filter_M
gaussianprocess4Clas
- 高斯过程是一种非参数化的学习方法，它可以很自然的用于regression，也可以用于classification。本程序用高斯过程实现分类！-Gaussian process is a non- parametric method of learning, it is very natural for regression. can also be used for classification. The procedures use
gaosi
- 多变量高斯过程样本的产生，用matlab编写的-Multivariate Gaussian process for selecting the samples, prepared using matlab
gpml-matlab-v3.1-2010-09-27
- 高斯过程算法在回归和分类中的应用程序。与书本《基于高斯过程的机器学习》配套。本程序是最新的v3.1版，更新于2010-09-27-Gaussian process regression and classification algorithm in the application. And the book " machine learning based on Gaussian process" support. T
GPRegression
- 讲解高斯过程回归的经典书籍.这里只包含第二章，讲解回归的部分-a book introduce the Gaussian Process Regression
IEEEtransactions_on-pattern-analysis
- 基于高斯过程的贝叶斯分类,详细介绍了高斯过程-Bayesian Classification With Gaussian Processes
列主元高斯消去法c++
- 利用c++语言实现了列主元高斯消去法求解方程组的过程。(Using c++ language to achieve the main element Gauss elimination method for solving equations process.)
GPR程序
- 基于高斯过程回归的锂电池充放电性能的预测(Prediction of Charge and Discharge Performance of Lithium Batteries Based on Gaussian Process Regression)
gpml
- 使用高斯过程构建主动学习算法，对个人相册集进行分类(An active learning algorithm is constructed using the Gauss process to categorize individual photo albums)
Autocorrelation
- 编写MATLAB程序，产生协方差函数为C(τ)=9??^(?10|??| )的零均值平稳高斯过程，产生一条样本函数.测量所产生样本的时间自相关函数，将结果与理论值比较。(Procedures for the preparation of MATLAB produced C covariance function (tau) =9^ (- 10||) zero mean stationary Gauss process to produc
GPstuff-4.7
- 高斯过程回归工具箱,其中包括高斯过程回归的基础例程，可用于分类，估计和预测(Gauss process regression toolbox, which includes the basic routines of Gauss process regression, can be used for classification, estimation and prediction)
GPR based on GPML-V4.1
- 基于 gpml-matlab-v4.1 工具箱，简单实现了高斯过程回归（Gaussian process regression，GPR）的多变量数据回归，给出了每个预测值的均值以及对应的方差。代码有详细的注释，附有训练数据和测试数据。(Based on the gpml-matlab-v4.1 toolbox, Gaussian process regression (GPR) multivariate data regression
Gaussian-process
- 高斯过程的编程实现预测，含有文档，程序，数据，以及参考文献。(Programming Gaussian process to achieve prediction, containing documents, programs, data, and references.)
锂电池退化GPR
- 高斯过程回归是一种基于贝叶斯原理的统计机器学习方法，将先验分布通过贝叶斯定理转化成后验分布，与其他没有采用贝叶斯技巧的预测方法而言，高斯过程最大的优点是能方便地推断出超参数，同时也能方便地给出预测值的置信区间(Gaussian Process Regression is a statistical machine learning method based on Bayesian principle. It transforms pr
gaussianprocess4Clas
- 用高斯过程的实现分类和回归的Matlab代码(Matlab code for implementing four classification and regression using Gauss process)
Code of GPs
- 实现高斯过程算法的一个简单回归，适合初学者学习。(A simple regression of the Gauss process algorithm is realized, which is suitable for beginners to learn.)