Description: MAPSAC指最大后验一致算法（Maximum a Posteriori sample consensus），是一种新的鲁棒性估计方法。由P.H.S Torr编写，供研究F阵鲁棒估计的人学习调用。-MAPSAC refers to maximum a posteriori agreement algorithm (Maximum a Posteriori sample consensus), is a new robust estimation method. By PHS Torr prepared for the study of robust estimation array F study call people. Platform: |
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Author:Zhongren Wang |
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Description: 在统计学中，最大后验（英文为Maximum a posteriori，缩写为MAP）估计方法根据经验数据获得对难以观察的量的点估计。它与最大似然估计中的 Fisher 方法有密切关系，但是它使用了一个增大的优化目标，这种方法将被估计量的先验分布融合到其中。所以最大后验估计可以看作是规则化（regularization）的最大似然估计。
-In statistics, the maximum a posteriori (English as a Maximum a posteriori, abbreviated as MAP) estimation method according to empirical data is difficult to obtain right amount of observation point estimate. It is with the maximum likelihood estimation of the Fisher method is closely related to, but it uses a larger optimization goals, this approach would be the estimated amount of integration of prior distribution to it. Therefore, maximum a posteriori estimates can be regarded as regularization (regularization) of the maximum likelihood estimate. Platform: |
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Author:youxia |
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Description: 针对视频序列的超分辨率重建,提出了一种动态自适应滤波方法. 在最大后验概率估计和加权最小二乘
的基础上,给出视频序列超分辨率重建数学模型 深入研究了运动补偿矩阵和权值矩阵的构成和性质 详细推导了
自适应滤波器的递推公式 分析了算法的存储与计算复杂度. 仿真实验表明该算法的重建结果相当有效,相比双三
次插值和无运动补偿的单帧迭代重建,可以获得一定的PSNR 增益 与Elad 滤波方法相比,具有更小的计算量和
更强的自适应性和鲁棒性.-Super-resolution for the reconstruction of video sequence, a dynamic adaptive filter. The maximum a posteriori probability estimation and weighted least squares, based on the super-resolution reconstruction of video sequence is given mathematical model in-depth study of the motion compensation matrix and weighted matrix composition and properties detailed derivation of the adaptive filter recurrence formula analysis of algorithms for the storage and computational complexity. Simulation results show that reconstruction of the algorithm very effective, compared to bicubic interpolation and non- Iterative reconstruction of single-frame motion compensation, allowed a certain PSNR gain and Elad filtering method, the calculation has a smaller volume and greater adaptability and robustness. Platform: |
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Author:redxuech |
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Description: EM算法Matlab实现。最大期望（EM）算法是在概率（probabilistic）模型中寻找参数最大似然估计或者最大后验估计的算法，其中概率模型依赖于无法观测的隐藏变量（Latent Variable）-EM algorithm by Matlab. Maximum expected (EM) algorithm is probabilistic (probabilistic) model to find maximum likelihood parameter estimation or maximum a posteriori estimation algorithm, probabilistic model which can not be observed depends on the hidden variable (Latent Variable) Platform: |
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Author:adhw |
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Description: 基于期望最大化(EM)的最大后验信道估计算法(MAP)在高信噪比(SNR)下将很难获得较低的估计误差,并且,对于导频辅助的MIMO-OFDM系统,OFDM符号的数据传输效率随着发送天线的增加而明显下降.为改善这两种缺陷,引入一种等效的信号模型来改善高SNR下的估计性能 在相邻多个OFDM符号内使用相移正交导频序列和联合估计来提高系统的数据传输效率和估计性能 根据角域内信道间的独立性来减小噪声对估计的影响.通过仿真实验可知,所提算法具有更小的估计误差和更高的数据传输效率.-Maximum a posteriori(MAP) channel estimation algorithm usually uses expectation maximum(EM) algorithm to decrease the high computation.However,this kind of operation has a difficulty in obtaining ideal estimation performance at high signal to noise ratio(SNR) because of the convergent feature of EM algorithm.In addition,for pilot-based multiple-input multiple-output with orthogonal frequency division multiplexing(MIMO-OFDM) systems,data transmission efficiency of OFDM symbol will be reduced with the increas... Platform: |
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Author:王睿 |
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Description: 在重建超分辨率图像后会产生振铃现象，此论文用于优化Pocs方法-Maximum a posteriori and maximum likelihood estimation method of comparison, comparing their respective advantages Platform: |
Size: 321536 |
Author:罗国中 |
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Description: 对F分布运行函数求条件期望估计和最大后验估计且做出图形-Run function to the conditional expectations estimates and maximum a posteriori estimation and graphics to make the F distribution Platform: |
Size: 1024 |
Author:shenzhou |
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Description: 在统计计算中，最大期望（EM）算法是在概率（probabilistic）模型中寻找参数最大似然估计或者最大后验估计的算法，其中概率模型依赖于无法观测的隐藏变量（Latent Variable）。最大期望经常用在机器学习和计算机视觉的数据聚类（Data Clustering）领域。
-In the statistical calculations, the maximum expected (EM) algorithm parameter maximum likelihood estimates or maximum a posteriori estimation algorithm to find the probability (probabilistic) model, in which the probability model is dependent on unobservable hidden variables (Latent Variable). Maximum expected areas often used in machine learning and computer vision, data clustering (Data Clustering). Platform: |
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Author:梦含 |
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Description: Bayesian Deblurring with Integrated Noise Estimation-Bayesian Deblurring with Integrated Noise Estimation
Conventional non-blind image deblurring algorithms
involve natural image priors and maximum a-posteriori
(MAP) estimation. As a consequence of MAP estimation,
separate pre-processing steps such as noise estimation and
training of the regularization parameter are necessary to
avoid user interaction. Moreover, MAP estimates involving
standard natural image priors have been found lacking in
terms of restoration performance. To address these issues
we introduce an integrated Bayesian framework that unifies
non-blind deblurring and noise estimation, thus freeing the
user of tediously pre-determining a noise level. A samplingbased
technique allows to integrate out the unknown noise
level and to perform deblurring using the Bayesian minimum
mean squared error estimate (MMSE), which requires
no regularization parameter and yields higher performance
than MAP estimates when combined with a learned highorder
image prior. A quan Platform: |
Size: 904192 |
Author:孙文义 |
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Description: 对信号进行检测和估计，对信号进行
最大后验估计和最大似然估计-The signal detection and estimation, the signal
Maximum a posteriori estimation and maximum likelihood estimation Platform: |
Size: 61440 |
Author:陈雪 |
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Description: 对于Iris数据集的Bayes分类器，采用最大后验概率进行判断。-Iris Bayes classifier for data sets, using maximum a posteriori estimation judgment. Platform: |
Size: 5120 |
Author:杨杨 |
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Description: This article contains analyses of the performance of various carrier synchronization
loops for offset quadrature phase-shift-keying (OQPSK) modulation, all
motivated in one form or another by the maximum a posteriori (MAP) estimation
of carrier phase. When they are implemented as either high or low signal-to-noise
ratio (SNR) approximations to the generic implementation suggested by the MAP
estimation of carrier phase for an OQPSK signal, it is shown that the loops behave
more like biphase than quadriphase loops in that they only exhibit a 180-deg phase
ambiguity rather than the 90-deg phase ambiguity typical of the latter. Platform: |
Size: 450560 |
Author:Alexandr |
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Description: 包含光伏电池模块、MPPT模块、BOOST模块、逆变模块，vKDErGS参数最大似然（ML）准则和最大后验概率（MAP）准则，对HARQ系统的吞吐量分析，虚拟力的无线传感网络覆盖，VHxSyct条件部分实现了追踪测速迭代松弛算法，现代信号处理中谱估计在matlab中的使用。- PV modules contain, MPPT module, BOOST module, inverter module, vKDErGS parameter Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, HARQ throughput analysis of the system, Virtual power wireless sensor network coverage, VHxSyct condition Partially achieved tracking speed iterative relaxation algorithm, Modern signal processing used in the spectral estimation in matlab. Platform: |
Size: 5120 |
Author:abhnef |
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Description: matlab开发工具箱中的支持向量机，igahZPy参数是路径规划的实用方法，最大似然（ML）准则和最大后验概率（MAP）准则，是国外的成品模型，fFEVXrr条件均值便宜跟踪的示例，现代信号处理中谱估计在matlab中的使用。- matlab development toolbox support vector machine, igahZPy parameter Is a practical method of path planning, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, Foreign model is finished, fFEVXrr condition Example tracking mean cheap, Modern signal processing used in the spectral estimation in matlab. Platform: |
Size: 10240 |
Author:zhyfpr |
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Description: 基于互功率谱的时延估计，MgrbwIK参数调试通过可以使用，各种资源分配算法实现，多目标跟踪的粒子滤波器，reKSVVD条件对于初学者具有参考意义，最大似然（ML）准则和最大后验概率（MAP）准则。- Based on the time delay estimation of power spectrum, MgrbwIK parameter Debugging can be used, Various resource allocation algorithm, Multi-target tracking particle filter, reKSVVD condition For beginners with a reference value, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion. Platform: |
Size: 4096 |
Author:cpwnyy |
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Description: 使用最大后验概率的超分辨算法来实现图像是复原-Using the maximum a posteriori estimation algorithm to achieve super-resolution image is restored Platform: |
Size: 5120 |
Author:本 |
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Description: Matlab implementation of the EM and MCMC algorithm for SVMs as introduced in the paper Data augmentation for support vector machines http://ba.stat.cmu.edu/journal/2011/vol06/issue01/polson.pdf-This is a Matlab implementation of the fancy idea by Polson & Scott that reformulates the traditional binary linear SVM problem into a MAP (Maximum a Posteriori) estimation in a probabilistic generative model, and by use of the technique of data augmentation, makes it possible to do very easy and fast Gibbs sampling for the solution. Platform: |
Size: 7168 |
Author:saisai |
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Description: 在心电信号处理过程中，为了避免产生Gibbs 振荡现象和严重的频率混叠现象，提出一种基于双树复小波变换，并结合最大后验估计确定阈值的心电信号去噪方法。文中采用了信噪比和均方误差来评价双树复小波变换和离散小波变换两种方法对心电信号的去噪效果。实验结果表明: 与传统离散小波变换相比，双树复小波变换去噪更彻底，边界、纹理等特征能较好地保留，可以作为一种生物医学信号降噪处理的新方法。-In ECG signal processing， in order to avoid the phenomena of Gibbs oscillation and severe frequency aliasing，a new ECG signal denoising algorithm is presented，which is based on dual-tree complex wavelet transform and combined with the maximum a posteriori estimation to determine the threshold． The signal-to-noise ratio and mean square error are used to uate the denoising effects of the dual-tree complex wavelet transform and discrete wavelet transform． The experimental result shows that compared with traditional discrete wavelet transform， the dual-tree complex wavelet transform reduces noise more thoroughly and retains boundary and texture characteristics better． The dualtree complex wavelet transform can be used as a new denoising method for biomedical signal denoising processing． Platform: |
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Author:kiel |
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Description: 在统计计算中，最大期望（EM）算法是在概率（probabilistic）模型中寻找参数最大似然估计或者最大后验估计的算法，其中概率模型依赖于无法观测的隐藏变量（Latent Variable）。最大期望经常用在机器学习和计算机视觉的数据聚类（Data Clustering）领域。(In statistical calculation, the expectation maximization (EM) algorithm in probability (probabilistic) maximum likelihood estimation and maximum a posteriori estimation algorithm for parameters in the model, the probability model depends on unobservable latent variable (Latent Variable). Maximum expectations are often used in machine learning and computer vision for data clustering (Data, Clustering) fields.) Platform: |
Size: 1024 |
Author:橡树
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