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A DT-CNN Data-Flow Implementation

Malki, Suleyman LU and Spaanenburg, Lambert LU (2008) 11th International Workshop on Cellular Neural Networks and Their Applications p.17-22
Abstract
Digital implementations of Cellular Neural Networks are studied in terms of their communication requirements. Secure and reliable communication seems to imply close control, which degrades performance. We introduce a mechanism that removes the need for explicit local network control, taking the internal network communication out of the performance equation. This allows handling boundary conditions without introducing additional cells and facilitates multi-level implementations. A typical feature extraction task in hand vein recognition shows a 20x performance improvement for the Cellular Neural Network implementation.
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
2008 11TH INTERNATIONAL WORKSHOP ON CELLULAR NEURAL NETWORKS AND THEIR APPLICATIONS
pages
17 - 22
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
11th International Workshop on Cellular Neural Networks and Their Applications
conference dates
2008-07-14 - 2008-07-16
external identifiers
  • wos:000260249200012
  • scopus:51949101500
language
English
LU publication?
yes
id
ef6f7dbc-4a45-4712-9f6a-8a9692bf121c (old id 1284083)
date added to LUP
2016-04-04 11:58:08
date last changed
2022-01-29 22:41:53
@inproceedings{ef6f7dbc-4a45-4712-9f6a-8a9692bf121c,
  abstract     = {{Digital implementations of Cellular Neural Networks are studied in terms of their communication requirements. Secure and reliable communication seems to imply close control, which degrades performance. We introduce a mechanism that removes the need for explicit local network control, taking the internal network communication out of the performance equation. This allows handling boundary conditions without introducing additional cells and facilitates multi-level implementations. A typical feature extraction task in hand vein recognition shows a 20x performance improvement for the Cellular Neural Network implementation.}},
  author       = {{Malki, Suleyman and Spaanenburg, Lambert}},
  booktitle    = {{2008 11TH INTERNATIONAL WORKSHOP ON CELLULAR NEURAL NETWORKS AND THEIR APPLICATIONS}},
  language     = {{eng}},
  pages        = {{17--22}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{A DT-CNN Data-Flow Implementation}},
  year         = {{2008}},
}