Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/379957
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | ||
dc.date.accessioned | 2022-05-12T08:58:23Z | - |
dc.date.available | 2022-05-12T08:58:23Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/379957 | - |
dc.description.abstract | newline | |
dc.format.extent | ||
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Multi layer tree liquid state machine recurrent auto encoder and elman deep neural network for improving classification accuracy | |
dc.title.alternative | ||
dc.creator.researcher | M Saktheeswari | |
dc.subject.keyword | Computer Science Artificial Intelligence | |
dc.subject.keyword | encoder and elman deep neural network for improving classification accuracy | |
dc.subject.keyword | Multi layer tree liquid state machine recurrent auto | |
dc.description.note | ||
dc.contributor.guide | T Balasubramanian | |
dc.publisher.place | Salem | |
dc.publisher.university | Periyar University | |
dc.publisher.institution | Department of Computer Science | |
dc.date.registered | 2016 | |
dc.date.completed | 2021 | |
dc.date.awarded | 2022 | |
dc.format.dimensions | 92mm | |
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Computer Science |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 72.38 kB | Adobe PDF | View/Open |
02_certificate.pdf | 121.15 kB | Adobe PDF | View/Open | |
03_priliminary pages.pdf | 1.12 MB | Adobe PDF | View/Open | |
04_chapter 1.pdf | 678.46 kB | Adobe PDF | View/Open | |
05_chapter 2.pdf | 480.91 kB | Adobe PDF | View/Open | |
06_chapter 3.pdf | 637.97 kB | Adobe PDF | View/Open | |
07_chapter 4.pdf | 657.09 kB | Adobe PDF | View/Open | |
08_chapter 5.pdf | 1.54 MB | Adobe PDF | View/Open | |
09_chapter 6.pdf | 184.26 kB | Adobe PDF | View/Open | |
10_bibliography.pdf | 487.88 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 256.15 kB | Adobe PDF | View/Open |
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