Diversified learning for continuous hidden Markov models with application to fault diagnosis
作者：
Highlights：
• The diversified learning formulas of CHMM parameters are derived.
• A likelihood-based model averaging estimator is developed.
• Bearing fault diagnosis is effectively performed.
摘要
•The diversified learning formulas of CHMM parameters are derived.•A likelihood-based model averaging estimator is developed.•Bearing fault diagnosis is effectively performed.
论文关键词：Continuous hidden Markov models,Fault diagnosis,Diversified gradient descent algorithm,Likelihood-based model averaging
论文评审过程：Received 1 November 2014, Revised 14 August 2015, Accepted 15 August 2015, Available online 20 August 2015, Version of Record 3 September 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.08.027
