Bayesian maximum a posterior DOA estimator based on importance sampling (ISBM) is proposed.

提出了基于重要性抽样的贝叶斯最大后验概率方位估计方法。

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Bayesian maximum a posterior DOA estimator based on Gibbs sampling (GSBM) is further investigated.

进一步研究了基于吉布斯抽样的贝叶斯最大后验概率方位估计方法。

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Finally, maximum a posterior (MAP) criterion is used to select the optimal segmentation result from all candidate segmentation results.

根据最大后验概率准则，选出最优的切分结果。

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Then the segmentation problem is formulated as Maximum a Posterior Probability (MAP) estimation rule.

分割问题可以被转换成一种最大后验概率估计问题。

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In this paper, a new joint Maximum a Posterior (MAP) formulation was proposed to integrate image registration into blind image Super-Resolution (SR) reconstruction to reduce image registration errors.

为了减小配准误差对盲超分辨率重建的影响，提出了一种影像配准和盲超分辨率重建联合处理的模型与方法。

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In this paper, a new joint Maximum a Posterior (MAP) formulation was proposed to integrate image registration into blind image Super-Resolution (SR) reconstruction to reduce image registration errors.

为了减小配准误差对盲超分辨率重建的影响，提出了一种影像配准和盲超分辨率重建联合处理的模型与方法。

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