A novel RSW&TST framework of MCPs detection for abnormal pattern recognition on large-scale time series and pathological signals in epilepsy

To quickly and efficiently recognize abnormal patterns from large-scale time series and pathological signals in epilepsy, this paper presents here a preliminary RSW&TST framework for Multiple Change-Points (MCPs) detection based on the Random Slide Window (RSW) and Trigeminal Search Tree (TST) m...

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Detalles Bibliográficos
Autores principales: Qi, Jinpeng, Zhu, Ying, Pu, Fang, Zhang, Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8694460/
https://www.ncbi.nlm.nih.gov/pubmed/34936654
http://dx.doi.org/10.1371/journal.pone.0260110

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8694460/
https://www.ncbi.nlm.nih.gov/pubmed/34936654
http://dx.doi.org/10.1371/journal.pone.0260110

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