A Tutorial on HMMs. 5. Advantage of HMM on Sequential Data ... Model Toolkit). – HMM toolbox for Matlab ... Speech recognition and segmentation. • Gesture .-A Tutorial on HMMs. 5. Advantage of HMM on Sequential Data ... Model Toolkit). – HMM too

A Tutorial on HMMs. 5. Advantage of HMM on Sequential Data ... Model Toolkit). – HMM toolbox for Matlab ... Speech recognition and segmentation. • Gesture .-A Tutorial on HMMs. 5. Advantage of HMM on Sequential Data ... Model Toolkit). – HMM too

EM 算法是求参数极大似然估计的一种方法，它可以从非完整数据集中对参数进行估计，是一种非常简单实用的学习算法。这种方法可以广泛地应用于处理缺损数据、截尾数据以及带有噪声等所谓的不完全数据，可以具体来说，我们可以利用EM算法来填充样本中的缺失数据、发现隐藏变量的值、估计HMM中的参数、估计有限混合分布中的参数以及可以进行无监督聚类等等。-Expectation Maximization image segmentation Input: ima: gr

数据模型归一化，模态振动，完整的基于HMM的语音识别系统，粒子图像分割及匹配均为自行编制的子例程。- Normalized data model, modal vibration, Complete HMM-based speech recognition system, Particle image segmentation and matching subroutines themselves are prepared.