Implementation of CNN computing technology

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

3 Citations (Scopus)

Abstract

The various physical implementations of the CNN Universal Machine architecture (analogic and digital VLSI, optical, optoelectronic) make the CNN paradigm a practically important new area of computing. For the VLSI implementations, application and prototyping systems have been developed. The new CNN algorithms can be programmed via a high level language, hence, their use does not require special skill of understanding the details. This language and compiler is embedded in the usual digital microprocessor or Personal Computer/Workstation environment. Some real life applications have already been developed, including a mammogram diagnostic system, a microscopy toolkit for chromosome analysis, intelligent multifunction fax machines, some video compression algorithms, etc. A new device, called the CNN Visual Mouse was also designed.

Original languageEnglish
Title of host publicationArtificial Neural Networks - ICANN 1997 - 7th International Conference, Proceeedings
EditorsWulfram Gerstner, Alain Germond, Martin Hasler, Jean-Daniel Nicoud
PublisherSpringer Verlag
Pages1151-1155
Number of pages5
ISBN (Print)3540636315, 9783540636311
Publication statusPublished - Jan 1 1997
Event7th International Conference on Artificial Neural Networks, ICANN 1997 - Lausanne, Switzerland
Duration: Oct 8 1997Oct 10 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1327
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Conference on Artificial Neural Networks, ICANN 1997
CountrySwitzerland
CityLausanne
Period10/8/9710/10/97

    Fingerprint

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Roska, T. (1997). Implementation of CNN computing technology. In W. Gerstner, A. Germond, M. Hasler, & J-D. Nicoud (Eds.), Artificial Neural Networks - ICANN 1997 - 7th International Conference, Proceeedings (pp. 1151-1155). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1327). Springer Verlag.