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  5. Efficient Concurrent Error Detection and Correction of Soft Errors in NTT-based Convolutions
 
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Efficient Concurrent Error Detection and Correction of Soft Errors in NTT-based Convolutions

Author(s)
O'Donnell, Anne  
Bleakley, Chris J.  
Reviriego, P.  
Maestro, J.A.  
Uri
http://hdl.handle.net/10197/3935
Date Issued
2009-06
Date Available
2012-11-28T13:11:54Z
Abstract
A system for soft error detection and correction is proposed for digital Integrated Circuit (IC) implementation of convolution. The convolution is implemented in a Residue NumberSystem using Fermat Number Theoretic Transforms. The flexibility afforded by the Modified Overlap Technique in allowing transforms of differing lengths in a convolution makes it possible to easily detect and correct soft errors by means of a Single Redundant Channel and pattern matching technique. The proposed system gives area reductions in the majority of cases examined, when compared with Triple Modular Redundancy. In the case of large (e.g. 28 and 32 bit) word lengths, the proposed system provides area reductions of up to 30%.
Other Sponsorship
University College Dublin
Type of Material
Conference Publication
Publisher
The Institution of Engineering and Technology
Copyright (Published Version)
2009 The Institution of Engineering and Technology
Subjects

Convolution

Digital integrated ci...

Error correction

Error detection

Pattern matching

Residue number system...

Subject – LCSH
Convolutions (Mathematics)
Error-correcting codes (Information theory)
Digital integrated circuits
Signal processing
DOI
10.1049/cp.2009.1724
Language
English
Status of Item
Peer reviewed
Journal
Signals and Systems Conference (ISSC 2009), IET Irish [proceedings]
Conference Details
20th IET Irish Signals and Systems Conference (ISSC), Dublin, Ireland, June, 2009
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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odonnell_bleakley_reviriego_maestro_2009.pdf

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253.63 KB

Format

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Checksum (MD5)

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Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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