Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/459465
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | ||
dc.date.accessioned | 2023-02-17T05:50:19Z | - |
dc.date.available | 2023-02-17T05:50:19Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/459465 | - |
dc.description.abstract | newline | |
dc.format.extent | xix, 120p. | |
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | An efficient deep learning algorithm for brain wave signal classification | |
dc.title.alternative | ||
dc.creator.researcher | Perumal Rani T | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Computer Science Information Systems | |
dc.subject.keyword | Engineering and Technology | |
dc.description.note | ||
dc.contributor.guide | Heren Chellam G | |
dc.publisher.place | Tirunelveli | |
dc.publisher.university | Manonmaniam Sundaranar University | |
dc.publisher.institution | Department of Information Technology and Engineering | |
dc.date.registered | ||
dc.date.completed | 2022 | |
dc.date.awarded | 2022 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Centre for Information Technology and Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 59.66 kB | Adobe PDF | View/Open |
03_contents.pdf | 88.92 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 71.04 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 323.51 kB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 272.49 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 217.47 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 392.14 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 293.77 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 338.32 kB | Adobe PDF | View/Open | |
11_chapter 7.pdf | 137.51 kB | Adobe PDF | View/Open | |
12_references.pdf | 229.52 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 72.4 kB | Adobe PDF | View/Open |
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