Analogue adaptive neural network circuit
Resource
Circuits, Devices and Systems, IEE Proceedings G
Journal
Circuits, Devices and Systems, IEE Proceedings G
Pages
-
Date Issued
1991-12
Date
1991-12
Author(s)
DOI
0956-3768
Abstract
Current integrated circuits realising neural networks take up too much area for implementing synapses. The paper presents a one-transistor (1T) synapse circuit that uses a single MOS transistor, which is more efficient for VLSI implementation of adaptive neural networks, compared to other synapse circuits. This 1T synapse circuit can be used to implement multiply/divide/sum circuits to realise an adaptive neural network. The feasibility of using this circuit in adaptive neural networks is demonstrated by a 4-bit analogue-to-digital converter circuit, based on the Hopfield modified neural network model, with an analogue LMS adaptive feedback. DC and transient studies show that 1T synapse circuits with an analogue adaptive feedback circuit can be used more efficiently for VLSI implementation of adaptive neural networks.
Subjects
Control systems, Adaptive; Integrated circuits, VLSI; Semiconductor devices, MOS; Transistors, Field effect; Adaptive neural networks; Analog neural networks; Hopfield networks; MOS transistors; One-transistor circuits; Neural networks
Type
journal article
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