The University of Southampton
University of Southampton Institutional Repository

Power Aware Learning for Class AB Analogue VLSI Neural Network

Modi, Sankalp, Wilson, Peter and Brown, Andrew (2006) Power Aware Learning for Class AB Analogue VLSI Neural Network At IEEE International Symposium on Circuits and Systems (ISCAS 2006), Greece. 21 - 24 May 2006.

Record type: Conference or Workshop Item (Paper)


Recent research into Artificial Neural Networks (ANN) has highlighted the potential of using compact analogue ANN hardware cores in embedded mobile devices, where power consumption of ANN hardware is a very significant implementation issue. This paper proposes a learning mechanism suitable for low-power class AB type analogue ANN that not only tunes the network to obtain minimum error, but also adaptively learns to reduce power consumption. Our experiments show substantial reductions in the power budget (30% to 50%) for a variety of example networks as a result of our power-aware learning.

PDF iscas_photo_ready_sub.pdf - Other
Download (234kB)

More information

Published date: 2006
Additional Information: Event Dates: May 21-24, 2006
Venue - Dates: IEEE International Symposium on Circuits and Systems (ISCAS 2006), Greece, 2006-05-21 - 2006-05-24
Keywords: Artificial Neural Networks, ANN hardware, Low-power, Power-aware, learning
Organisations: EEE


Local EPrints ID: 262564
PURE UUID: eed41e27-8a04-47b3-b803-2a14eb413a0d

Catalogue record

Date deposited: 12 May 2006
Last modified: 18 Jul 2017 08:50

Export record


Author: Sankalp Modi
Author: Peter Wilson
Author: Andrew Brown

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.