A4 Refereed article in a conference publication

A mixed-mode array computing architecture for online dictionary learning




AuthorsJussi H. Poikonen, Mika Laiho

Conference nameIEEE International Symposium on Circuits and Systems

PublisherInstitute of Electrical and Electronics Engineers Inc.

Publication year2017

Book title 2017 IEEE International Symposium on Circuits and Systems (ISCAS)

Journal name in sourceProceedings - IEEE International Symposium on Circuits and Systems

First page 1

Last page4

Number of pages4

ISBN978-1-4673-6852-0

ISSN0271-4302

DOIhttps://doi.org/10.1109/ISCAS.2017.8050589(external)


Abstract

We recently mapped an algorithm for online learning of linear subspaces
using local learning rules to an analog array computing framework. In
this work we consider a simplified version of this algorithm which can
be realized as a mixed-mode computing array. This allows similar
learning results as the unmodified algorithm and is designed to allow
large-scale test circuit fabrication with commercially available
technologies. We demonstrate by numerical simulations of the mixed mode
learning system that less than ten-bit resolution in the considered
digital circuitry is sufficient for useful learning; such resolution
allows efficient implementation of the related analog computations. The
presented circuit has practical applications e.g. in signal
classification, adaptive compression, and compressive sensing in
low-power devices.



Last updated on 2024-26-11 at 20:36