Abstract
Cellular Neural Networks (CNN) is a massive computing paradigm which became very popular in the last decades. A Cellular Neural Network Universal Machine is an extension of the CNN concept. An implementation of CNN-UM on Field Programmable Gate Arrays (FPGA) appears attractive because their full computational power comes to a life only in hardware. Besides FPGA there are many different possibilities to implement a CNN-UM. The following questions will be answered while reading this paper: What is the CNN paradigm? Which application areas are of interest and what requirements are to meet? What is a CNN-UM? Which ways are possible to implement a CNN-UM - what are the differences? Which problems occur while implementing a CNN-UM on FPGA?
Original language | American English |
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Title of host publication | VXV International Symposium on Theoretical Engineering |
Pages | 1-5 |
Number of pages | 5 |
Publication status | Published - 24 Jun 2009 |
Event | VXV International Symposium on Theoretical Engineering - Lübeck, Germany Duration: 22 Jun 2009 → 24 Jun 2009 |
Conference
Conference | VXV International Symposium on Theoretical Engineering |
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Period | 22/06/09 → 24/06/09 |