分割问题可以被转换成一种最大后验概率估计问题。
Then the segmentation problem is formulated as Maximum a Posterior Probability (MAP) estimation rule.
实验结果表明最大后验概率估计算法也能高效重建出高质量图像。
The experimental results show that the MAP algorithm can be able to efficiently reconstruct a high quality image.
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。
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.
依据这一模型，该方法使用贝叶斯理论和领域约束获得了区域和边界的最大后验概率估计。
The method is to derive the maximum a posteriori estimate of the regions and the boundaries by using Bayesian inference and neighborhood constraints based on Markov random fields(MRFs) models.
采用最大似然估计或最大后验概率准则，用估计值来取代前面等式中的真实值。
Either the maximum likelihood estimate or the maximum a posteriori estimate may be used in place of the exact value in the above equations.
对于解码状态参数，通过计算最大后验转移概率的方法作最佳估计，井给出了一种简化的计算方法。
The codec state is also estimated by computing the maximum posterior transition probabilities, with a simplified computing method described.
对于解码状态参数，通过计算最大后验转移概率的方法作最佳估计，并给出了一种简化的估计方法。
The codec states were estimated by computing the maximum posterior transition probabilities with a simplified computing method.
针对传统的支持向量机方法不能提供后验概率的输出问题，从信息熵的角度采用最大熵估计方法，直接对支持向量机输出进行后验概率建模。
To the problem that the standard SVM does not provide probabilities output, the probabilistic outputs for support vector machines is modeled based on the maximum entropy estimation.
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。
Bayesian maximum a posterior DOA estimator based on Gibbs sampling (GSBM) is further investigated.
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。
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。
Bayesian maximum a posterior DOA estimator based on importance sampling (ISBM) is proposed.
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