Intrinsic Hardware Evolution of Neural Networks in Reconfigurable Analogue and Digital Devices

Authors:
J Maher;B Mc Ginley;P Rocke;F Morgan
Affiliations:
National University of Ireland, Galway;National University of Ireland, Galway;National University of Ireland, Galway;National University of Ireland, Galway
Venue:
FCCM '06 Proceedings of the 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Year:
2006

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Abstract

Bio-Inspired concepts such as evolution and learning have attracted much attention recently because of a growing interest in automatic design of complex systems [1]. The classic XOR problem has been used as a benchmark application by researchers. In this paper a Genetic Algorithm has been developed to evolve a Neural Network (NN) implementation of a two input XOR function. This GA will subsequently be used to contrast the relative difficulties of implementing the XOR NN on FPGA's and FPAA's respectively. Two case studies are presented to demonstrate intrinsic evolution of the XOR network on reconfigurable analogue and digital devices. In both cases the GA evolves the synaptic weights and threshold values for an NN implemented on both Field Programmable Gate Array (FPGA) and Field Programmable Analogue Array (FPAA) hardware platforms.