Açık Akademik Arşiv Sistemi

Signal Processing and Communications Applications Conference

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dc.contributor.authors Karagoz, Y; Gul, S; Cetinel, G;
dc.date.accessioned 2020-02-27T07:00:58Z
dc.date.available 2020-02-27T07:00:58Z
dc.date.issued 2017
dc.identifier.citation Karagoz, Y; Gul, S; Cetinel, G; (2017). Signal Processing and Communications Applications Conference. 2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), , -
dc.identifier.issn 2165-0608
dc.identifier.uri https://hdl.handle.net/20.500.12619/64870
dc.description.abstract At signal processing stage, after preprocessing step for eye movements (vertical, horizontal and blink) maximum and minimum voltage amplitude values are detected. These values are directly determine the performance of the classification process. K-Nearest Neighbor (k-NN) classifier and Support Vector Machines (SVM) are used for classification. According to the results, k-NN and SVM perform the classification task with %90.3 and %92.6 accuracy, respectively. Simulation results show that with the proposed EOG based HMI system, physically limited patients can communicate with their environments in a successful manner.
dc.language Turkish
dc.publisher IEEE
dc.subject Telecommunications
dc.title Signal Processing and Communications Applications Conference
dc.type Proceedings Paper
dc.contributor.department Sakarya Üniversitesi/Adapazarı Meslek Yüksekokulu/Elektronik Ve Otomasyon Bölümü
dc.contributor.saüauthor Gül, Sevda
dc.contributor.saüauthor Çetinel, Gökçen
dc.relation.journal 2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
dc.identifier.wos WOS:000413813100235
dc.contributor.author Yurdagul Karagoz
dc.contributor.author Gül, Sevda
dc.contributor.author Çetinel, Gökçen


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