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Application of Analogue Amorphous Silicon Memory Devices to Resistive Synapses for Neural Networks
Published online by Cambridge University Press: 21 February 2011
Abstract
The amorphous silicon memory device shows promise as an analogue weight element in neural networks. The device resistance can be programmed to within 5% of any specific value between lkΩ and lMΩ using 10ns to 1μ voltage pulses in the range 1–5V. In this paper we describe the physical structure of the element and its electrical characteristics. Finally, a simple example is discussed of a small neural network implementing the EXOR function using amorphous silicon memory elements as a resistive array of weights and external op-amps as the current summing nodes.
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- Copyright © Materials Research Society 1992
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