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Efficiency considerations for DT-CNN hardware

Malki, Suleyman LU and Spaanenburg, Lambert LU (2007) MWSCAS p.189-192
Abstract
Cellular Neural Networks have become a popular paradigm for modeling nonlinear systems. First-hand implementations are in software on floating-point platforms for pure performance, while programmable analog circuitry has been tested for embedded low-power applications. The paper discusses gradual algorithmic and structural improvements that bring efficient digital hardware into consideration. This provides 32-bits floating-point accuracy on a block-scaled 12-bits fixed-point platform.
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Proceedings MWSCAS NEWCAS
pages
189 - 192
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
MWSCAS
conference dates
0001-01-02
external identifiers
  • wos:000257283200049
  • scopus:50049129992
language
English
LU publication?
yes
id
320234db-d179-4691-83b1-953e159a78de (old id 603741)
date added to LUP
2016-04-04 11:55:43
date last changed
2022-01-29 22:36:32
@inproceedings{320234db-d179-4691-83b1-953e159a78de,
  abstract     = {{Cellular Neural Networks have become a popular paradigm for modeling nonlinear systems. First-hand implementations are in software on floating-point platforms for pure performance, while programmable analog circuitry has been tested for embedded low-power applications. The paper discusses gradual algorithmic and structural improvements that bring efficient digital hardware into consideration. This provides 32-bits floating-point accuracy on a block-scaled 12-bits fixed-point platform.}},
  author       = {{Malki, Suleyman and Spaanenburg, Lambert}},
  booktitle    = {{Proceedings MWSCAS NEWCAS}},
  language     = {{eng}},
  pages        = {{189--192}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Efficiency considerations for DT-CNN hardware}},
  year         = {{2007}},
}