Coercively Adjusted Auto Regression Model for Forecasting in Epilepsy EEG

Recently, data with complex characteristics such as epilepsy electroencephalography (EEG) time series has emerged. Epilepsy EEG data has special characteristics including nonlinearity, nonnormality, and nonperiodicity. Therefore, it is important to find a suitable forecasting method that covers thes...

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Detalles Bibliográficos
Autores principales: Kim, Sun-Hee, Faloutsos, Christos, Yang, Hyung-Jeong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3655454/
https://www.ncbi.nlm.nih.gov/pubmed/23710252
http://dx.doi.org/10.1155/2013/545613

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3655454/
https://www.ncbi.nlm.nih.gov/pubmed/23710252
http://dx.doi.org/10.1155/2013/545613

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