This paper proposes a generic method for finding non-propagating Cellular Neural Network (CNN) templates that can be implemented reliably on a given CNN Universal Machine chip. The method has two main components: (i) adaptive optimization of templates based on measurements of actual CNN chips; (ii) simplification and decomposition of Boolean operators into a sequence of simpler ones that work correctly and more robustly on a given chip. Examples are presented using two concrete stored-program CNNUM chips to demonstrate the effectiveness of the proposed method, whose advantages and limitations are also discussed.
|Number of pages||6|
|Publication status||Published - Jan 1 1998|
|Event||Proceedings of the 1998 5th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA - London, UK|
Duration: Apr 14 1998 → Apr 17 1998
|Other||Proceedings of the 1998 5th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA|
|Period||4/14/98 → 4/17/98|
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