A digitally programmable current mode analog shunting inhibition cellular neural network

Amine Bermak, Farid Boussa Èdand Abdesselam Bouzerdoum

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A novel read-out and column circuit for VLSI implementation of a Shunting Inhibition Cellular Neural Network (SICNN) is proposed. Image enhancement and edge detection based on SICNN with programmable mask size are achieved within a CMOS imager. In contrast to most existing implementations, the circuit is based on a mixed analog digital approach in which the read-out is realized using a digital circuit while the processing takes advantage of the compactness and low power of the current mode approach. The mask size and coef®cients can be varied with a digitally programmable current mode analog processor. In addition, the pixel output and the processed SICNN output are obtained simultaneously on the -y resulting in a real-time computation of SICNN. The imager has been fabricated using 0.7 μm CMOS technology.

Original languageEnglish
Title of host publicationICECS 2000 - 7th IEEE International Conference on Electronics, Circuits and Systems
Pages962-965
Number of pages4
Volume2
DOIs
Publication statusPublished - 2000
Externally publishedYes
Event7th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2000 - Jounieh, Lebanon
Duration: 17 Dec 200020 Dec 2000

Other

Other7th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2000
CountryLebanon
CityJounieh
Period17/12/0020/12/00

    Fingerprint

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Bermak, A., & Bouzerdoum, F. B. È. A. (2000). A digitally programmable current mode analog shunting inhibition cellular neural network. In ICECS 2000 - 7th IEEE International Conference on Electronics, Circuits and Systems (Vol. 2, pp. 962-965). [913036] https://doi.org/10.1109/ICECS.2000.913036