Abstract
Cellular Neural/Nonlinear Networks (CNN) are analog, non-linear, mainly locally connected processor arrays placed on a multidimensional grid. In this tutorial the general framework and some application areas are described, mainly for mathematicians and physicists. The new invention, the CNN Universal Machine is exposed as well; its unique capability of implementing stored-programmable nonlinear spatial dynamics is highlighted. Finally, the first silicon VLSI implementations providing enormous computing power (in the order of 1012 operations per second on a single chip) are reviewed.
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