Description: 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 Platform: |
Size: 1024 |
Author:Xiubin Dai |
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Description: 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 iterative method which alternates between performing an expectation (E) step, which computes the expectation of the log-likelihood evaluated using the current estimate for the latent variables, and a maximization (M) step, which computes parameters maximizing the expected log-likelihood found on the E step. These parameter-estimates are then used to determine the distribution of the latent variables in the next E step.-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 iterative method which alternates between performing an expectation (E) step, which computes the expectation of the log-likelihood evaluated using the current estimate for the latent variables, and a maximization (M) step, which computes parameters maximizing the expected log-likelihood found on the E step. These parameter-estimates are then used to determine the distribution of the latent variables in the next E step.
Platform: |
Size: 2048 |
Author:loossii |
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Description: 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. Platform: |
Size: 9216 |
Author:孙磊 |
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Description: 状态模型的极大似然估计，使用EM算法，以及卡尔曼滤波。-This supplementary note discusses the maximum likelihood esti-mation of state space models using Expectation-Maximization (EM) algorithm and
bootstrap procedure for statistical inference. A Matlab program script implement-ing the Kalman ¯ lter, Kalman smoother and EM algorithm Platform: |
Size: 2048 |
Author:陈静雅 |
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