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Fault tolerant CNN template design and optimization based on chip measurements

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5 Author(s)
P. Foldesy ; Lab. of Analogical & Neural Comput., Hungarian Acad. of Sci., Budapest, Hungary ; L. Kek ; T. Roska ; A. Zarandy
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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 stored-program CNNUM chips to demonstrate the effectiveness of the proposed method, whose advantages and limitations are also discussed

Published in:

Cellular Neural Networks and Their Applications Proceedings, 1998 Fifth IEEE International Workshop on

Date of Conference:

14-17 Apr 1998