搜索资源列表
Bayesian
- this the doc related to the Bayesian Inference for Dynamic Models with Dirichlet Process Mixtures-this is the doc related to the Bayesian Inference for Dynamic Models with Dirichlet Process Mixtures
bayes
- 贝叶斯决策理论：根据先验概率、类分布密度函数以及后验概率这些量来实现分类决策的方法.最小错误率的贝叶斯决策：根据一个事物后验概率最大作为分类依据的决策 -Bayesian decision theory: According to the a priori probability, the class distribution as well as the posterior probability density function of these values in order to a
1
- bayesian sequential state estimation for mimo wireless communications
Bayesian_approach_to_digital_matting
- importance of bayesian approach is described clearly and comparison done with many other methods.
Bayesian
- 贝叶斯分类器的算法解析，以及用c#写的关于文本文档的贝叶斯算法设计-Bayesian classifier algorithm analysis, and use c# to write the text of the document on Bayesian Algorithm
BCS-in-WSN
- 无线传感网络中，压缩感知数据恢复的一种贝叶斯分析，也许能用于分布式压缩感知-Wireless sensor networks, compressed sensing data recovery of a Bayesian analysis, may be used for distributed compressed sensing
A-Bayesian-Approach
- In this paper, we propose a Bayesian methodology for receiver function analysis, a key tool in determining the deep structure of the Earth’s crust.We exploit the assumption of sparsity for receiver functions to develop a Bayesian deconvolution
BAYESIAN-HIGH-PRIORITY-REGION-GROWING-FOR-CHANGE-
- BAYESIAN HIGH PRIORITY REGION GROWING FOR CHANGE
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
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
New-folder-(3)
- the program based on particle filter for a new algorithm, Integrated Bayesian MCMC Model Selection MONTE CARLO that Ma Erkefu chain
Approximate-Bayesian-Inference-for-Robust-Speech-
- Speech processing applications such as speech enhancement and speaker identification rely on the estimation of relevant parameters from the speech signal. These parameters must often be estimated from noisy observations since speech signals are r
paper2
- A Bayesian approach to sparse channel estimation in OFDM systems
NassarAlexandraINSA
- Natural Image Segmentation textured locally melt Bayesian local segmentation into two classes
MICCAI09_David
- Bayesian Maximal Paths for Coronary Artery Segmentation 3D CT Angiograms-Bayesian Maximal Paths for Coronary Artery Segmentation 3D CT Angiograms
Irace_RFIA_2012
- A Bayesian mixture model Poisson-Gamma laws to segment PET images
paper2
- Receiver-based Recovery of Clipped OFDM Signals for PAPR Reduction A Bayesian Approach
paper5
- Application of Bayesian Hierarchical Prior Modeling to Sparse Channel Estimation
paper2
- Block Bayesian Sparse Learning Algorithms With Application to Estimating Channels in OFDM Systems