Anomaly detection in invasively recorded neuronal signals using deep neural network: effect of sampling frequency

Fabietti, M. ORCID: 0000-0003-3093-5985, Mahmud, M. ORCID: 0000-0002-2037-8348 and Lotfi, A. ORCID: 0000-0002-5139-6565, 2021. Anomaly detection in invasively recorded neuronal signals using deep neural network: effect of sampling frequency. In: M. Mahmud ORCID: 0000-0002-2037-8348, M. Shamim Kaiser, N. Kasabov, K. Iftekharuddin and N. Zhong, eds., Applied Intelligence and Informatics: first international conference, AII 2021, Nottingham, UK, July 30–31, 2021, Proceedings. Communications in Computer and Information Science (1435). Cham: Springer International Publishing, pp. 79-91. ISBN 9783030822682

Full text not available from this repository.
Item Type: Chapter in book
Description: Paper presented at 2021 International Conference on Applied Intelligence and Informatics (AII 2021), Nottingham, July 30–31, 2021.
Creators: Fabietti, M., Mahmud, M. and Lotfi, A.
Publisher: Springer International Publishing
Place of Publication: Cham
Date: July 2021
Number: 1435
ISBN: 9783030822682
Identifiers:
NumberType
10.1007/978-3-030-82269-9_7DOI
1456994Other
Divisions: Schools > School of Science and Technology
Record created by: Laura Ward
Date Added: 16 Aug 2021 13:22
Last Modified: 16 Aug 2021 13:22
URI: http://irep.ntu.ac.uk/id/eprint/43988

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