Show simple item record

A comparative evaluation of time-delay, deep learning and echo state neural networks when used as simulated transhumeral prosthesis controllers

dc.contributor.authorDay, Charles R.
dc.contributor.authorChadwick, Edward K.
dc.contributor.authorBlana, Dimitra
dc.date.accessioned2022-10-27T23:05:53Z
dc.date.available2022-10-27T23:05:53Z
dc.date.issued2020-09-28
dc.identifier179469654
dc.identifierb724f261-3b83-4452-95c1-72b62f126566
dc.identifier85093852158
dc.identifier.citationDay , C R , Chadwick , E K & Blana , D 2020 , A comparative evaluation of time-delay, deep learning and echo state neural networks when used as simulated transhumeral prosthesis controllers . in 2020 International Joint Conference on Neural Networks : IJCNN 2020 - Proceedings . , 9206772 , Proceedings of the International Joint Conference on Neural Networks , Institute of Electrical and Electronics Engineers Inc. , 2020 International Joint Conference on Neural Networks, IJCNN 2020 , Virtual, Glasgow , United Kingdom , 19/07/20 . https://doi.org/10.1109/IJCNN48605.2020.9206772en
dc.identifier.citationconferenceen
dc.identifier.isbn9781728169262
dc.identifier.issn2161-4393
dc.identifier.otherORCID: /0000-0003-0877-5110/work/83311021
dc.identifier.otherORCID: /0000-0003-0488-6120/work/83311028
dc.identifier.urihttp://aura-test.abdn.ac.uk/handle/2164/19236
dc.descriptionACKNOWLEDGMENT The authors are grateful to ten anonymous, able-bodied, human participants who participated in the recording of all of the datasets used to train and test the above neural networks.en
dc.format.extent7
dc.format.extent823824
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof2020 International Joint Conference on Neural Networksen
dc.relation.ispartofseriesProceedings of the International Joint Conference on Neural Networksen
dc.subjectEcho State Networksen
dc.subjectLong Short-Term Memoryen
dc.subjectTime-Delay Neural Networksen
dc.subjecttime-series processingen
dc.subjecttranshumeral prosthesis controlen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectSoftwareen
dc.subjectArtificial Intelligenceen
dc.subject.lccQA75en
dc.titleA comparative evaluation of time-delay, deep learning and echo state neural networks when used as simulated transhumeral prosthesis controllersen
dc.typeConference itemen
dc.contributor.institutionUniversity of Aberdeen.Engineeringen
dc.contributor.institutionUniversity of Aberdeen.Medical Sciencesen
dc.contributor.institutionUniversity of Aberdeen.Other Applied Health Sciencesen
dc.contributor.institutionUniversity of Aberdeen.Centre for Health Data Scienceen
dc.contributor.institutionUniversity of Aberdeen.Aberdeen Centre for Health Data Scienceen
dc.contributor.institutionUniversity of Aberdeen.Grampian Data Safe Haven (DaSH)en
dc.identifier.doihttps://doi.org/10.1109/IJCNN48605.2020.9206772
dc.date.embargoedUntil2022-09-28
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85093852158&partnerID=8YFLogxKen


Files in this item

Thumbnail
Name:
Chen_etal_IEEE_Multi_Attention ...
Size:
4.738Mb
Format:
PDF
View/Open

This item appears in the following Collection(s)

Show simple item record