Search - expected maximum algorithm

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[matlab] GMM-GMR-v1.2 DL : 0: 这是一款用matlab编写的GMM算法，有样例，实现用EM算法寻找GMM参数-This is a matlab prepared using GMM algorithm, there is a sample, look for implementation using EM algorithm for GMM parameter
Date : 2025-07-12 Size : 39kb User : Ruby
[matlab] EMALGORITHM DL : 0: 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.
Date : 2025-07-12 Size : 2kb User : loossii
[AI-NN-PR] EM DL : 0: EM算法Matlab实现。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）-EM algorithm by Matlab. Maximum expected (EM) algorithm is probabilistic (probabilistic) model to find maximum likelihood parameter estimation or maximum a posteriori estimation algorithm, probabilistic model which can not be observed depends on the hidden variable (Latent Variable)
Date : 2025-07-12 Size : 49kb User : adhw
[Algorithm] em DL : 0: 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 the statistical calculations, the maximum expected (EM) algorithm parameter maximum likelihood estimates or maximum a posteriori estimation algorithm to find the probability (probabilistic) model, in which the probability model is dependent on unobservable hidden variables (Latent Variable). Maximum expected areas often used in machine learning and computer vision, data clustering (Data Clustering).
Date : 2025-07-12 Size : 3.28mb User : 梦含
[AI-NN-PR] fenci DL : 0: 运用正向最大匹配算法和反向最大匹配算法，在已有预料库的基础上实现中文分词-The maximum matching algorithm using forward and reverse maximum matching algorithm, the library has been implemented on the basis of expected Chinese word
Date : 2025-07-12 Size : 3.98mb User : 吴佩
[AI-NN-PR] em1 DL : 0: 使用最大期望算法可以在概率模型中寻找参数最大似然估计。-Using the maximum expected algorithm can seek parameters of maximum likelihood estimation in the probabilistic model
Date : 2025-07-12 Size : 1kb User :
[Software Engineering] flat_array_dbf DL : 0: 面阵的幅度相位全控制自适应数字波束形成算法——对角加载 QRD-SMI 算法的研究；两种面阵唯相位(Phase-Only)数字波束形成算法——小相位扰动约束算法和期望方向增益最大约束算法的研究；面阵的数字多波束形成算法——二维 FFT 多波束的研究，以及 FFT 在可编程逻辑器件中的实现。 -Research of the adaptive digital beamforming algorithm, which control both amplitude and phase of each array element: diagonal loading QRD-SMI algorithm. ② Research of two Phase-Only DBF algorithms: small phase perturbation restriction algorithm and maximum gain of the expected direction restriction algorithm. ③ Research of multiple beams algorithm for planar array: 2D-FFT multiple beams. And the realization of FFT with CPLD.
Date : 2025-07-12 Size : 3.25mb User : 313039
[Graph Recognize] EMSeg DL : 0: EM算法，即最大期望算法，用于图像分割，测试可用- EM算法，即最大期望算法，用于图像分割，测试可用 EM algorithm, the maximum expected algorithm for image segmentation, testing available
Date : 2025-07-12 Size : 31kb User : 李严