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| 001 | 878546 | ||
| 005 | 20250129092416.0 | ||
| 024 | 7 | _ | |a 10.1109/EMS.2017.16 |2 doi |
| 024 | 7 | _ | |a WOS:000434813800005 |2 WOS |
| 037 | _ | _ | |a FZJ-2020-02905 |
| 100 | 1 | _ | |a Chen, Tao |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 111 | 2 | _ | |a 2017 UKSim-AMSS 11th European Modelling Symposium (EMS) |c Manchester |d 2017-11-20 - 2017-11-21 |w United Kingdom |
| 245 | _ | _ | |a Model-Driven Development Methodology Applied to Real-Time MEG Signal Preprocessing System Design |
| 260 | _ | _ | |c 2017 |b IEEE |
| 295 | 1 | 0 | |a 2017 European Modelling Symposium (EMS) : [Proceedings] - IEEE, 2017. - ISBN 978-1-5386-1410-5 - doi:10.1109/EMS.2017.16 |
| 300 | _ | _ | |a 28-33 |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
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| 336 | 7 | _ | |a Output Types/Conference Paper |2 DataCite |
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| 336 | 7 | _ | |a Contribution to a book |0 PUB:(DE-HGF)7 |2 PUB:(DE-HGF) |m contb |
| 520 | _ | _ | |a Model-based system engineering (MBSE) provides a high-level environment and efficiently handles the ever-rising complexity of computation and control systems. We introduce a requirement-driven, model-based development methodology (RDD & MBD) for real-time computation systems based on vendor neutral specifications. The proposed development methodology focuses on the use of Systems Modeling Language (SysML) to define high-level model-based design descriptions for later implementation in heterogeneous hardware/software systems. In magnetoencephalography (MEG) data processing, biological artifacts in particular overtop the signal of interest by orders of magnitude and must be removed from the measured signals to avoid reconstruction errors. However, many real-time brain computer interface (BCI) approaches neglect real-time artifact removal as it is computationally demanding. Therefore, we applied the RDD & MBD approach to the design of a system-on-chip (SoC), capable of performing real-time artifact rejection, based on the recently presented method 'Ocular and Cardiac Artifact rejection for Real-Time Analysis in MEG' (OCARTA). |
| 536 | _ | _ | |a 573 - Neuroimaging (POF3-573) |0 G:(DE-HGF)POF3-573 |c POF3-573 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef Conference |
| 700 | 1 | _ | |a Suslov, Sergey |0 P:(DE-Juel1)133946 |b 1 |u fzj |
| 700 | 1 | _ | |a Schiek, Michael |0 P:(DE-Juel1)133935 |b 2 |u fzj |
| 700 | 1 | _ | |a Shah, N. Jon |0 P:(DE-Juel1)131794 |b 3 |u fzj |
| 700 | 1 | _ | |a Waasen, Stefan van |0 P:(DE-Juel1)142562 |b 4 |u fzj |
| 700 | 1 | _ | |a Dammers, Jurgen |0 P:(DE-Juel1)131757 |b 5 |u fzj |
| 773 | _ | _ | |a 10.1109/EMS.2017.16 |
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| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Decoding the Human Brain |1 G:(DE-HGF)POF3-570 |0 G:(DE-HGF)POF3-573 |2 G:(DE-HGF)POF3-500 |v Neuroimaging |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |
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