A Dedicated Multi-Chip Programmable System for Cellular Neural Networks

Authors:
Mario Salerno;Fausto Sargeni;Vincenzo Bonaiuto
Affiliations:
University of Rome “Tor Vergata”, Department of Electronic Engineering, Via di Tor Vergata-00133, Rome, Italy;University of Rome “Tor Vergata”, Department of Electronic Engineering, Via di Tor Vergata-00133, Rome, Italy sargeni@uniroma2.it;University of Rome “Tor Vergata”, Department of Electronic Engineering, Via di Tor Vergata-00133, Rome, Italy
Venue:
Analog Integrated Circuits and Signal Processing - Special issue on Learning on Silicon
Year:
1999

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Abstract

Cellular Neural Networks (CNN’s) represent a remarkable improvement in the hardware implementation of Artificial Neural Networks (ANN’s). In fact, their regular structure and their local connectivity feature contribute to render this class of neural networks especially appealing for VLSI implementations. CNNs are widely applied in several fields, including image processing and pattern recognition. In this research, the authors already presented two fully digitally programmable CNN chips with 3×3 (3×3DPCNN chip) and 6×6 cells (6×6DPCNN chip) respectively. In this paper, a system with twenty of the latter chips will be presented. The main features of this electronic system consist of the full digital programmability of the templates, the digital input/output for logic operations, the analog outputs for dynamic analysis and the implementation of space-variant as well as space-invariant CNNs.