A pattern recognition framework for detecting dynamic changes on cyclic time series

DOI10.1016/J.PATCOG.2014.08.017zbMath1373.68320OpenAlexW1985715791MaRDI QIDQ1677199

Per Ask, Ankica Babic, Arash Gharehbaghi

Publication date: 10 November 2017

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2014.08.017

zbMATH Keywords

time serieshybrid modelcyclic time seriesphonocardiogramsystolic murmurs

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

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• Sequence classification via large margin hidden Markov models
• Semi-supervised clustering with discriminative random fields
• A boosting approach for supervised Mahalanobis distance metric learning
• Support-vector networks
• Support Vector Machine Training for Improved Hidden Markov Modeling

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