摘要
隐马尔可夫模型是序列数据处理和统计学习的一种重要概率模型,已被成功应用于许多工程任务中。首先介绍了隐马尔可夫模型的基本原理,接着综述了其在人的行为分析、网络安全和信息抽取中的最新应用。最后对最近提出来的无限状态隐马尔可夫模型的原理及最新发展进行了总结。
Hidden Markov Model （HMM） is an important probabilistic model of sequential data processing and statistical study. It has already been successfully applied in many projects in practice. Firstly, this paper introduces the basic principles of the Hidden Markov Model, and then gives a review to its latest application in the human activity analysis, network security and information extraction. Finally it summarizes the theory and latest progress of the recently proposed infinite Hidden Markov Model （iHMM）.
出处
《计算机系统应用》
2010年第7期255-259,216,共6页
Computer Systems & Applications
