Stovold, James Henry and O'Keefe, Simon Edward Marius orcid.org/0000-0001-5957-2474 (2017) Reaction–diffusion chemistry implementation of associative memory neural network. International Journal on Parallel, Emergent and Distributed Systems. pp. 74-94. ISSN 1744-5760
Abstract
Unconventional computing paradigms are typically very difficult to program. By implementing efficient parallel control architectures such as artificial neural networks, we show that it is possible to program unconventional paradigms with relative ease. The work presented implements correlation matrix memories (a form of artificial neural network based on associative memory) in reaction–diffusion chemistry, and shows that implementations of such artificial neural networks can be trained and act in a similar way to conventional implementations.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2016 Informa UK Limited, trading as Taylor & Francis Group. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details. |
Keywords: | artificial neural network,Associative memory,correlation matrix memory,reaction–diffusion chemistry,unconventional computing |
Dates: |
|
Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Depositing User: | Pure (York) |
Date Deposited: | 06 Jun 2017 16:00 |
Last Modified: | 13 Mar 2025 05:23 |
Published Version: | https://doi.org/10.1080/17445760.2016.1155579 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1080/17445760.2016.1155579 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:117428 |
Download
Filename: Reaction_diffusion_chemistry_implementation_of_associative_memory_neural_network.pdf
Description: Reaction diffusion chemistry implementation of associative memory neural network