BriefGPT.xyz
Sep, 2008
使用非负矩阵分解学习隐马尔科夫模型
Learning Hidden Markov Models using Non-Negative Matrix Factorization
HTML
PDF
George Cybenko, Valentino Crespi
TL;DR
本文提出了一种基于高阶马尔可夫统计的非负矩阵分解的HMM学习算法，该算法支持对HMM的循环状态数目进行估计，并迭代非负矩阵分解算法以改善学习到的HMM参数。
Abstract
The
baum-welsh algorithm
together with its derivatives and variations has been the main technique for learning
hidden markov models
(HMM) from observational data. We present an HMM learning algorithm based on the
→