Recursive cellular nonlinear neural networks for ultra-low noise digital arithmetic
dc.contributor.advisor | Jullien, Graham | |
dc.contributor.advisor | Haslett, James W. | |
dc.contributor.author | Yebjoah, Jonathan Johnson | |
dc.date.accessioned | 2005-08-16T17:34:57Z | |
dc.date.available | 2005-08-16T17:34:57Z | |
dc.date.issued | 2004 | |
dc.description | Bibliography: p. 63-66 | en |
dc.description | Some pages are in colour. | en |
dc.format.extent | xiv, 113 leaves : ill. ; 30 cm. | en |
dc.identifier.citation | Yebjoah, J. J. (2004). Recursive cellular nonlinear neural networks for ultra-low noise digital arithmetic (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/14808 | en_US |
dc.identifier.doi | http://dx.doi.org/10.11575/PRISM/14808 | |
dc.identifier.isbn | 0494037369 | en |
dc.identifier.lcc | AC1 .T484 2004 Y43 | en |
dc.identifier.uri | http://hdl.handle.net/1880/42154 | |
dc.language.iso | eng | |
dc.publisher.institution | University of Calgary | en |
dc.publisher.place | Calgary | en |
dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | |
dc.title | Recursive cellular nonlinear neural networks for ultra-low noise digital arithmetic | |
dc.type | master thesis | |
thesis.degree.discipline | Electrical and Computer Engineering | |
thesis.degree.grantor | University of Calgary | |
thesis.degree.name | Master of Science (MSc) | |
ucalgary.thesis.notes | UARC | en |
ucalgary.thesis.uarcrelease | y | en |
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