I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Prediction of Pathological Tremor Signals Using Long Short-..:
Pascual-Valdunciel, Alejandro
;
Lopo-Martínez, V
;
Sendra-Arranz, R
...
Publisher's version. , 2022
Link:
http://hdl.handle.net/10261/295494
RT Journal T1
Prediction of Pathological Tremor Signals Using Long Short-Term Memory Neural Networks
UL https://suche.suub.uni-bremen.de/peid=base-ftcsic:oai:digital.csic.es:10261_295494&Exemplar=1&LAN=DE A1 Pascual-Valdunciel, Alejandro A1 Lopo-Martínez, V A1 Sendra-Arranz, R A1 González-Sánchez, M A1 Pérez-Sánchez, J.R A1 Grandas, Francisco A1 Torricelli, Diego A1 Moreno, J.C A1 Barroso, Filipe O A1 Pons, José Luis A1 Gutierrez, A PB IEEE YR 2022 K1 Machine learning K1 LSTM K1 peripheral electrical stimulation K1 tremor prediction K1 essential tremor JF Publisher's version LK http://hdl.handle.net/10261/295494 DO http://hdl.handle.net/10261/295494 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)