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Conference papers

Building a 2D-compatible multilayer neural network

Bernard Girau 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : Neural computation paradigms may be defined to counterbalance the topological problems of digital hardware implementations of neural networks. The use of such paradigms naturally leads to neural models that are more tolerant of hardware constraints. A theoretical and practical framework called FPNA aims at developing such neural architectures that are easy to map onto FPGAs, thanks to a simplified topology and an original data exchange scheme. These Field Programmable Neural Arrays reconcile the high connection density of neural architectures with the need of a limited interconnection scheme in hardware implementations. This paper focuses on the FPNA-based simplification of the architecture of a multilayer shortcut perceptron used in a pattern classification problem.
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Submitted on : Tuesday, September 26, 2006 - 8:51:18 AM
Last modification on : Friday, February 4, 2022 - 3:33:16 AM


  • HAL Id : inria-00099137, version 1



Bernard Girau. Building a 2D-compatible multilayer neural network. International Joint Conference on Neural Networks, Jul 2000, none, 6 p. ⟨inria-00099137⟩



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