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 prepa

利用贝叶斯原理估计混合logit模型的参数，有循环检测，周期性检测，最大似然（ML）准则和最大后验概率（MAP）准则。- Bayesian parameter estimation principle mixed logit model, There are cycle detection, periodic testing, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion.

最大似然（ML）准则和最大后验概率（MAP）准则，最小均方误差（MMSE）的算法，通过虚拟阵元进行DOA估计。- Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, Minimum mean square error (MMSE) algorithm, Conducted through virtual array DOA estimation.

通过反复训练模板能有较高的识别率，最大似然（ML）准则和最大后验概率（MAP）准则，现代信号处理中谱估计在matlab中的使用。- Through repeated training XHNrrYGlate have higher recognition rate, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, Modern signal processing used in the spec

要对单变量正态分布以及分类分布两种概率分布 模型，分别采用最大似然（ML），最大后验（MAP）以及贝叶斯估计（Bayes）的 方法进行概率密度估计。 -In this paper, the maximum likelihood (ML), maximum a posteriori (MAP) and Bayesian estimation (Bayes) methods are used to estimate the probability density of two kinds of pr