Second-Order Hidden Markov Models Based on the Fuzzy C-Means and Fuzzy Entropy

摘要：

Second-order hidden Markov models (HMM2) have been widely used in pattern recognition, especially in speech recognition. Their main advantages are their capabilities to model noisy temporal signals of variable length. This paper presents an extension of HMM2 based on the fuzzy c-means (FCM) and fuzzy entropy (FE) referred to as FCM-FE-HMM2. By building up a generalised fuzzy objective function, several new formulae solving model training problem are theoretically derived for FCM-FE-HMM2.

关键词： second-order hidden Markov models forward-backward procedure Baum-Welch algorithm fuzzy c-means fuzzy entropy

作者: Du Shiping Wang Jian Wei Yuming

作者单位: Collge of Biology and Science Sichuan Agricultural University Yaan 625014, Sichuan ,China Collge of Biology and Science Sichuan Agricultural University Yaan 625014,Sichuan,China Triticeae Research Institute Sichuan Agricultural University Yaan 625014, Sichuan ,China

会议类型: 国际会议

会议名称: 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

会议地点: 厦门

会议语种:英文

页码: 49-52

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）