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Correctness of the FPNA neural paradigm

Bernard Girau 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Neural networks are usually considered as naturally parallel computing models. But the number of operators and the complex connection graphs of standard neural models can not be handled by digital hardware devices. A new theoretical and practical framework allows to reconcile simple hardware topologies with complex neural architectures: Field Programmable Neural Arrays (FPNA) lead to powerful neural architectures that are easy to map onto digital hardware, thanks to a simplified topology and an original data exchange scheme. This report describes the basic principles of the FPNA paradigm. Formal definitions are introduced and illustrated. Two computation methods for feedforward FPNAs are introduced. The proof of their correctness is sketched.
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Submitted on : Tuesday, September 26, 2006 - 8:50:18 AM
Last modification on : Friday, February 4, 2022 - 3:30:40 AM
Long-term archiving on: : Friday, November 25, 2016 - 11:47:42 AM


  • HAL Id : inria-00099071, version 1



Bernard Girau. Correctness of the FPNA neural paradigm. [Intern report] A00-R-023 || girau00o, 2000, 8 p. ⟨inria-00099071⟩



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