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用于估计未知数据的EM算法,即最大期望算法,用到的地方很多,可用来做同步。-The data used to estimate the unknown EM algorithm, that is the maximum expectation algorithm, used in many places, can be used for synchronization.
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关于最大似然重建方法的实现,可用于tomography reconstruction-This is the code for maximum likelihood expectation maximum reconstruction method which is frequently applied in tomography reconstruction, such as CT and PET
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This program is for image segmentation using Expectation maximum
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实际的场景,若电梯的最大载客量m=10,设电梯中已有的
客人服从0-10 之间的均匀分布,且电梯中的任意一人在任意一层下的
概率相同,若你在第三层需要乘电梯到第七层,电梯处在第一层,共
8 层。且在每一层等电梯到达他们的目的楼层的客人服从0-3 的均匀分
布此时我们对电梯的运行加一些限
制,即电梯中若有客人未达目的地,电梯不会改变运行方向,求直到
你到达第七层为止,,电梯需停次数的数学期望,并进行计算机模拟验
证。-The actual scene, if the m
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In statistics, an expectation-maximization (EM) algorithm is a method for finding maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. EM is an iterati
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求解参数估计的常用算法——EM,即期望最大化算法,用于代替样本量不完全时的极大似然估计算法。-Common algorithm for solving parameter estimation- EM, expectation maximization algorithm is used to replace the sample size is not completely at the maximum likelihood estimation algorithm.
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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) maximu
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最大期望方法实现的APES,两种方法,包括一维和二维方法(Maximum expectation methods are implemented in APES, and two methods are included, one and two dimensional methods)
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