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The idea of CNN processors was introduced by [[Leon Chua]] and Lin Yang in 1988.<ref>https://www.researchgate.net/publication/3183706_Cellular_neural_networks_Theory ("Cellular Neural Networks: Theory" and "Cellular Neural Networks: Applications" in IEEE Transactions on Circuits and Systems)</ref> In these articles, Chua and Yang outline the underlying mathematics behind CNN processors. They use this mathematical model to demonstrate, for a specific CNN implementation, that if the inputs are static, the processing units will converge, and can be used to perform useful calculations. They then suggest one of the first applications of CNN processors: image processing and pattern recognition (which is still the largest application to date). [[Leon O. Chua|Leon Chua]] is still active in CNN research and publishes many of his articles in the [[International Journal of Bifurcation and Chaos]], of which he is an editor. Both [[IEEE Circuits and Systems Society|IEEE Transactions on Circuits and Systems]] and the International Journal of Bifurcation also contain a variety of useful articles on CNN processors authored by other knowledgeable researchers. The former tends to focus on new CNN architectures and the latter more on the dynamical aspects of CNN processors.
In 1993, [[:nl:Tamás Roska|Tamas Roska]] and Leon Chua introduced the first algorithmically programmable analog CNN processor in the world.<ref name=":3">{{Cite journal|last1=Roska|first1=T.|last2=Chua|first2=L.O.|date=March 1993|title=The CNN universal machine: an analogic array computer|url=http://dx.doi.org/10.1109/82.222815|journal=IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing|volume=40|issue=3|pages=163–173|doi=10.1109/82.222815|issn=1057-7130|url-access=subscription}}</ref> The multi-national effort was funded by the [[Office of Naval Research]], the [[National Science Foundation]], and the [[Hungarian Academy of Sciences]], and researched by the Hungarian Academy of Sciences and the [[University of California, Berkeley|University of California]]. This article proved that CNN processors were producible and provided researchers a physical platform to test their CNN theories. After this article, companies started to invest into larger, more capable processors, based on the same basic architecture as the CNN Universal Processor. Tamas Roska is another key contributor to CNNs. His name is often associated with biologically inspired information processing platforms and algorithms, and he has published numerous key articles and has been involved with companies and research institutions developing CNN technology.
=== Literature ===
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