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.
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References
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© 1997 Springer-Verlag Berlin Heidelberg
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Roska, T. (1997). Implementation of CNN computing technology. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020306
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DOI: https://doi.org/10.1007/BFb0020306
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