Series in Microelectronics

edited by Wolfgang Fichtner
Qiuting Huang
Heinz Jäckel
Hans Melchior
George S. Moschytz
Gerhard Tröster

Drahoslav Lím

1^st edition 2002, 160 pages, € 64,00. ISBN 3-89649-504-6

A Cellular Neural Network (CNN) is a non-linear array of locally interconnected analog processors - cells - which operate in parallel. In this thesis we present an architecture suitable for implementing a programmable general purpose CNN processor. The architecture deals with some of the characteristics and restrictions inherent in VLSI technologies, and allows a multi-chip, mixed analog-digital hardware realization of a large, continuous-time CNN, with step-wise programmable cell interconnections, and a piece-wise linear output function. The design and implementation of the processor in CMOS technology are presented, followed by measured data and examples of CNN processing functions performed.

Drahoslav Lím received the MS degree in electrical engineering from the University of California, Irvine, in 1992, and the PhD in electrical engineering from the Swiss Federal Institute of Technology (ETH), Zurich, in 1998. In 1993 he joined the Information and Signal Processing Laboratory at the ETH as a research assistant, working with Prof. George S. Moschytz on the implementation of cellular neural networks. Since 1999 he has been working in the telecommunications industry.