a posteriori estimation
英 [ə ˌpɒsteriˈɔːraɪ ˌestɪˈmeɪʃn]
美 [ə ˌpoʊstɪriˈɔːri ˌestɪˈmeɪʃn]
网络 后验估计
双语例句
- In the paper, moving object segmentation algorithm based on mean field theory ( MFT) using maximum a posteriori estimation of Markov random field ( MRF-MAP) is proposed.
研究了基于均值场理论和马尔可夫场的运动目标分割方法。 - A posteriori error estimation on anisotropic mesh for Poisson equation
Poisson方程各向异性网格的后验误差估计 - A New Space Resection Method and a Posteriori weight Estimation
新的空间后方交会法及验后权的估计 - The application of a Gaussian Markov Random Fields ( GMRF) based Maximum A Posteriori Probability ( MAP) estimation for image Gaussian noise filter was presented.
提出了基于高斯马尔可夫随机场（GMRF）的最大后验概率（MAP）估计在图像高斯噪声滤波中的应用方法。 - A posteriori error estimation with finite element semi-discrete methods for Fourth Order Nonlinear Singular Parabolic Equations
四阶非线性奇异抛物方程的半离散有限元方法的后验误差估计 - A posteriori error estimation based on the stress super-convergence recovery technique is proposed.
根据有限元解的超收敛特性提出了一种基于应力超收敛恢复技术的广义特征值问题后验误差估计。 - In this paper, we proposed an EMM ( error minimum and maximum A posteriori estimation) method to restore the blurred image.
在本论文中，提出一种EMM（最小恢复残差和最大后验概率）方法进行模糊图像的盲恢复。 - The mathematical algorithm for map matching is presented in this paper. A maximum posteriori estimation model, i. e.
提出了地图匹配的数学框架，建立了地图匹配的极大验后估计模型，即MP模型，该模型能够最优的将原始位置观测值转化到路网上去。 - Point-spread function ( PSF) plays a key role in image restoration. As a result, prior knowledge and posteriori estimation of PSF is usually used to restore image.
在图像恢复技术中，点扩展函数（PSF）是影响图像恢复结果的关键因素，所以常常利用先验知识和后验判断方法估计PSF函数来恢复图像。 - According to this approach, a statistically based cost function through which phase unwrapping is treated as a maximum a posteriori probability ( MAP) estimation problem is defined.
从这一思路出发，一方面本文引入了基于极大验后估计（MAP）的统计费用优化指标函数，并给出了特定的应用模型； - On the Space Resection With Ground Coordinates as Weighted Observations and a Posteriori Weight Estimation
地面坐标作为带权观测值的空间后方交会与验后权估计 - According to Bayesian theory, the recovery of image denoise is transformed a problem of maximum a posteriori ( MAP) estimation. Finally, the experiment conclusion is obtained based on MAP rule.
根据Bayesian定理，图像降噪恢复问题能转化成一个最大后验（MAP）估计问题，并能够获得MAP准则下将超声图像降噪的恢复结果。 - This paper deals with the application of a posteriori variance estimation in space resection of a single photograph.
本文讨论了验后方差估计在单象空间后方交会中的应用。 - Kalman filtering deconvolution based on maximum a posteriori estimation
基于极大后验估计的卡尔曼滤波反褶积 - The segmentation problem is the maximizing a posteriori estimation of the set of object area result from the watershed labeled.
设计了一个先验密度惩罚图像当中分水线变换后的相似的区域，图像分割进而变成对目标子集的最大后验估计。 - Separating the sources by maximum a posteriori estimation.
用最大后验概率的估计方法分离源语音信号。 - We use Bayesian maximum a posteriori estimation training a speaker model from background model, to solve the problem of model miss matching in speaker verification system.
采用贝叶斯最大后验概率估计的方式，从统一背景模型中生成说话人模型。 - The reason that Block Discrete Cosine Transform ( BDCT) brings blocking artifacts is analyzed in this paper. An efficiently adaptive de-blocking algorithm is proposed based on maximum a posteriori estimation of Markov Random Field ( MRF-MAP) Frame.
分析了块离散余弦变换（BDCT）图像编码的块效应产生原因，基于马尔可夫随机场最大后验估计（MRF-MAP）框架提出了一种有效的自适应去块效应算法。 - A posteriori error estimation for reduced-basis method and FEM is proposed, and a method for constructing the reduced space based on greedy algorithm is studied.
提出了减基法与原有限元法之间的误差判断方法，研究了基于贪婪算法的减基空间构造方法。 - In the thesis, the optimal Kalman filter is deduced based on maximum a posteriori estimation criterion obtains from the Bayesian filtering, discusses the predict-revised autoregressive operation mechanism of the algorithm.
本文从贝叶斯滤波通式入手，推导了基于极大后验估计准则下的最优Kalman滤波，论述了算法预测-修正自回归的运行机制。 - In order to improve the reliability of soft information, a soft-output OSIC MMSE MIMO detector based a posteriori symbol probability estimation is proposed by taking consideration of residual interference cancellation errors. A complexity-reduced implementation is also provided.
为了提高输出的编码后比特软信息的可靠性，首先研究了理想信道估计下，基于后验符号概率估计、考虑残留干扰抵消误差的软输出OSICMMSEMIMO检测算法，给出了降低复杂度的实现方法。 - Model parameters for the learning algorithm, we give two different Bayesian estimation strategies: maximum a posteriori estimation and conditional expectation estimation.
对于算法中模型参数的学习，给出了两种不同的贝叶斯估计策略：最大后验估计和条件期望估计。 - The equalization algorithm based on maximum a posteriori ( MAP) estimation is the optimal algorithm which is based on the minimum probability of the error criterion, while the high complexity of the algorithm restricts its practical application.
信道均衡算法中，基于最大后验概率的均衡算法（maximumaposteriori）是基于平均错误概率最小准则下的最佳算法，但是算法的高复杂度缺点制约了其在实际中的应用。