搜索资源列表
Bayesian-Compressive-Sensing
- 基于贝叶斯压缩感知理论的相关介绍，压缩感知理论是近几年非常热门的研究内容-Introduction of compressed sensing theory based on Bayesian compressed sensing theory is very popular in recent years, the research content
bayesian-approximiation
- 贝叶斯估计近似计算方法的技术描述文档，讲解贝叶斯近似估计理论与方法-Bayesian estimation of the approximate calculation method of the technology described in the document, explaining Bayesian the approximate estimation theory and methods
routingwirelessnetworksBayesiangame
- 挺好的无线传感器网络关于贝叶斯判决进行路由的文章。-Fine articles on Bayesian routing of wireless sensor networks.
FECG-Extraction
- 胎儿心电信号提取，用贝叶斯方法，和神经网络接近。很详细！-FECG Extraction Using Bayesian Inference and Neural Networks Approximation
Short-duration-power_CS
- 根据压缩传感(Compressed Sensing，cs)N论，首次提出了短时电能质量扰动信号的压缩采样方法，该方法突破了奈奎斯特采样频率的限制，实现了低于奈奎斯特采样频率的低速率采样。文中对比分析了CS理论与传统采样理论，研究了cS短时电能质量信号压缩采样的实现方法，包括：测量矩阵的构建、稀疏基的选取和电能质量信号快速贝叶斯匹配追踪重构算法(FBMP)-Compressed sensing ( Compressed Sensing , cs ) N theory , first propose
Image-reconstruction_CS
- 合稀疏贝叶斯学习(SBL)和可压缩传感理论(CS)，给出一种在噪声测量条件下重建可压缩图像的方法。该方法将cS理论中图像重建过程看作一个线性回归问题，而待重建的图像是该回归模型巾的未知权值参数；利用sBL方法对权值赋予确定的先验条件概率分布用以限制模型的复杂度，并引入超参数- Hop sparse Bayesian learning ( SBL ) and compressible sensing theory ( CS ) , give a compressible image recon
moshishibie
- 对X应用贝叶斯分类，对X的前两类训练单层感知器-The classification of X application of Bias，on the X of two kinds of training single-layer perceptron
Naive-Bayes
- 本文从不同的角度出发，讨论并分析了三种改进朴素贝叶斯分类性能的方法。为进一步的研究打下坚实的基础。-In this paper, starting from a different perspective, to discuss and analyze the three improved Naive Bayesian classifier performance. Lay a solid foundation for further research.
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- 实现贝叶斯分类器,在matlab上的源代码-Bayesian classifier in matlab source code
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- 在matlab上实现的贝叶斯分类器，有缘吗-To achieve the matlab Bayesian classifier
NILPLS-yong-yu-mo-shi-fenlei
- 非线性迭代PLS信息模式识别算法,有和fisher，贝叶斯算法的比较。资料详细-Nonlinear Iterative PLS information pattern recognition algorithm, and fisher, Bayesian Algorithms. Detailed information
BP_nerual_network
- 通过gdm、LM以及贝叶斯正则化，进行BP神将网络-By gdm, LM and Bayesian regularization, for God BP Network
moshishibie
- 贝叶斯分类估计和最大似然估计的matlab编程-it is used to make the bayesis guji and the mle.it is very convenient for homework
calculate-sample
- c++程序来计算样本大小对成本效益试验基于贝叶斯框架-A C++ program to calculate sample sizes for cost-effectiveness trials in a Bayesian framework
afnichidnfs-
- 对五种典型的贝叶斯网分类器进行了分析与比较。在总结各种分类器的基础上，对它们进行了实验比较，讨论了各自的特点，提出了一种针对不同应用对象挑选贝叶斯网分类器的方法。 -Of five kinds of typical bayesian network classifiers are analyzed and compared. On the basis of summarizing the various classifiers, experiments have been carried out
Machine-Learning
- 机器学习的讲义和作业，包括了SVM、隐氏马尔科夫和朴素贝叶斯等方法，非常适合初学机器学习的人！-Machine learning lectures and assignments, including SVM, Hidden Markov and Naï ve Bayes methods, machine learning is ideal for beginners！
classificiation-algorithm-overview
- 机器学习领域经典分类算法综述，包括Decision Tree（ＩＤ３、C4.5(C5.0)、CART、PUBLIC、SLIQ和SPRINT算法），三种典型贝叶斯分类器（朴素贝叶斯算法、TAN算法、贝叶斯网络分类器），k-近邻 、 基于数据库技术的分类算法（ MIND算法、GAC-RDB算法），基于关联规则（CBA:Classification Based on Association Rule）的分类（Apriori算法），支持向量机分类，基于软计算的分类方法（粗糙集（rough set）、遗传
Bayesian-classifier
- 本实验基于贝叶斯分类器对采集的微博数据进行情感分析，从中提取出不同的情感类别。-In this study, Bayesian classifier based on the micro-blog sentiment analysis data were collected, extracted from different emotional categories.
Modelling-Functional
- 相关向量机用于分类，可用于稀疏贝叶斯学习的研究，文章内含有RVM代码-Relevance vector machine for classification, can be used to study the sparse Bayesian learning, the article contains RVM code
Sparsity-Inducing-DOA
- 基于稀疏分解的宽带信号DOA估计方法，使用了基于贝叶斯的方法具有良好的估计精度和分辨率-Wideband signal sparse decomposition DOA estimation method based on the use of a method based on Bayesian estimation has good accuracy and resolution