In search of a robust digital CNN system
(2006) 10th International Workshop on Cellular Neural Networks and their Applications (CNNA) p.328-333- Abstract
- Microelectronics promises a high component density and low power dissipation to embedded systems. Unfortunately such a component will always suffer from various error types that make the chip respond differently from its functional simulation. This is especially true for Cellular Neural Networks (CNN), which makes the determination of robust, low-precision parameters to guarantee small footprint and reliable operation an important design consideration. This paper describes the digital word width effects in a CNN implementation that must be considered to achieve a small size for a reliable system. It discusses the automated design space exploration using a Field-Programmable Gate-Array (FPGA) implementation to perform an optimal CNN... (More)
- Microelectronics promises a high component density and low power dissipation to embedded systems. Unfortunately such a component will always suffer from various error types that make the chip respond differently from its functional simulation. This is especially true for Cellular Neural Networks (CNN), which makes the determination of robust, low-precision parameters to guarantee small footprint and reliable operation an important design consideration. This paper describes the digital word width effects in a CNN implementation that must be considered to achieve a small size for a reliable system. It discusses the automated design space exploration using a Field-Programmable Gate-Array (FPGA) implementation to perform an optimal CNN parameters selection. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1409811
- author
- Fang, Wen Hai LU ; Wang, Cheng and Spaanenburg, Lambert LU
- organization
- publishing date
- 2006
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- automated design space exploration, digital word width effects, cellular neural networks, microelectronics, robust templates, embedded systems, field-programmable gate-array
- host publication
- Proceedings of the 2006 10th IEEE International Workshop on Cellular Neural Networks and Their Applications
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 10th International Workshop on Cellular Neural Networks and their Applications (CNNA)
- conference dates
- 2006-08-28 - 2006-08-30
- external identifiers
-
- wos:000245392200070
- scopus:47549086536
- ISBN
- 1-4244-0639-0
- DOI
- 10.1109/CNNA.2006.341654
- language
- English
- LU publication?
- yes
- id
- ac2bd5b0-6226-4b8c-bd01-099d537be380 (old id 1409811)
- date added to LUP
- 2016-04-04 10:22:33
- date last changed
- 2022-02-13 19:40:18
@inproceedings{ac2bd5b0-6226-4b8c-bd01-099d537be380, abstract = {{Microelectronics promises a high component density and low power dissipation to embedded systems. Unfortunately such a component will always suffer from various error types that make the chip respond differently from its functional simulation. This is especially true for Cellular Neural Networks (CNN), which makes the determination of robust, low-precision parameters to guarantee small footprint and reliable operation an important design consideration. This paper describes the digital word width effects in a CNN implementation that must be considered to achieve a small size for a reliable system. It discusses the automated design space exploration using a Field-Programmable Gate-Array (FPGA) implementation to perform an optimal CNN parameters selection.}}, author = {{Fang, Wen Hai and Wang, Cheng and Spaanenburg, Lambert}}, booktitle = {{Proceedings of the 2006 10th IEEE International Workshop on Cellular Neural Networks and Their Applications}}, isbn = {{1-4244-0639-0}}, keywords = {{automated design space exploration; digital word width effects; cellular neural networks; microelectronics; robust templates; embedded systems; field-programmable gate-array}}, language = {{eng}}, pages = {{328--333}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{In search of a robust digital CNN system}}, url = {{http://dx.doi.org/10.1109/CNNA.2006.341654}}, doi = {{10.1109/CNNA.2006.341654}}, year = {{2006}}, }