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Low Cost Neural Network Hardware for Control
Technical Paper
2001-01-3397
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Feedforward artificial neural networks are universal function approximators and inherently parallel computing structures. Because of the lack of appropriate hardware realisations, applications of neural networks are predominantly implemented as sequential programs on digital processors. In this paper we describe an analogue integrated circuit realisation of a local response neural network (LCNN) that achieves a high degree of parallel computation in a small size, low cost and low power consumption. Because it can directly receive analog inputs from sensors and output analog control signals to actuators it is well suited as a building block for real-time control systems.
Authors
Citation
Sitte, J., "Low Cost Neural Network Hardware for Control," SAE Technical Paper 2001-01-3397, 2001, https://doi.org/10.4271/2001-01-3397.Also In
SAE 2001 Transactions Journal of Passenger Cars - Electronic and Electrical Systems
Number: V110-7; Published: 2002-09-15
Number: V110-7; Published: 2002-09-15
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