Home /Research /Pulse stream VLSI neural networks
LEARNING

Pulse stream VLSI neural networks

Alan F. Murray, S. Churcher, Alister Hamilton, African Homes, G.B. Jackson, H. Martin Reekie, R. Woodburn

Year
1994
Citations
22

Abstract

EPSILON, a large, working, VLSI device, demonstrates pulse stream methods in the wider context of analog neural networks. EPSILON uses dynamic weight storage techniques, but a nonvolatile alternative is desirable. To that end, we have developed an amorphous silicon memory, which we present in experiments incorporating the device in a modest pulse stream neural chip. We have also developed a target-based training algorithm, which we demonstrate in a prototype learning device using a realistic problem. Finally, we explore system-level problems in experiments with a second version of EPSILON in a small, autonomous robot.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Keywords

Computer scienceVery-large-scale integrationArtificial neural networkContext (archaeology)Pulse (music)ChipRobotArtificial intelligenceEmbedded systemTelecommunications

Related papers

Browse all LEARNING papers