{"title":"Deep Learning of EEG Time-Frequency Representations for Identifying Eye States","authors":"Dharmendra Gurve, S. Krishnan","doi":"10.1142/S2424922X18400065","DOIUrl":null,"url":null,"abstract":"A new Convolutional Neural Network (CNN) architecture to classify nonstationary biomedical signals using their time–frequency representations is proposed. The present method uses the spectrogram of...","PeriodicalId":47145,"journal":{"name":"Advances in Data Science and Adaptive Analysis","volume":"36 1","pages":"1840006:1-1840006:13"},"PeriodicalIF":0.9000,"publicationDate":"2018-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Data Science and Adaptive Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/S2424922X18400065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 9
Abstract
A new Convolutional Neural Network (CNN) architecture to classify nonstationary biomedical signals using their time–frequency representations is proposed. The present method uses the spectrogram of...