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JOURNALS // Preprints of the Keldysh Institute of Applied Mathematics

Keldysh Institute preprints, 2018, 010, 20 pp. (Mi ipmp2371)

Cloud resource MathBrain for encephalography data analysis
E. S. Oplachko, S. D. Rykunov, M. N. Ustinin

References

1. Quarteroni A., Saleri F., Gervasio P., Scientific Computing with MATLAB and Octave, Texts in Computational Science and Engineering, Third Edition, 2014, 1–4  mathscinet
2. Ostenveld R., Fries P., “FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data”, Computational Intelligence and Neuroscience, 2011 (2011)  crossref
3. Stolk A., Todorovic A., “Online and offline tools for head movement compensation in MEG”, NeuroImage, 68 (2013), 39–48  crossref
4. Aguera P., Jerbi K., “ELAN: A Software Package for Analysis and Visualization of MEG, EEG, and LFP Signals”, Computational Intelligence and Neuroscience, 2011 (2011)  crossref
5. Campi C., Pascarella A., “Highly Automated Dipole EStimation (HADES)”, Computational Intelligence and Neuroscience, 2011 (2011)  crossref
6. Hamalainen M., MNE Software Overview, https://wiki.aalto.fi/download/attachments/40600812/MNE-manual-2.7.pdf, MGH/HMS/MIT Athinoula A. Martinos Center for Biomedical Imaging, 2009 (data obrascheniya 26.11.2017)
7. Francois T., Baillet S., “Brainstorm: A User-Friendly Application forMEG/EEG Analysis”, Computational Intelligence and Neuroscience, 2011 (2011)  crossref
8. Gramfort A., Papadopoulo A., Olivi E., “OpenMEEG: opensource software for quasistatic bioelectromagnetics”, BioMedical Engineering OnLine, 2010  crossref  elib
9. Gramfort A., Papadopoulo T., “Forward Field Computation with OpenMEEG”, Computational Intelligence and Neuroscience, 2011 (2011)  crossref  zmath
10. Delorme A., Makeig S., “EEGLAB: an open source toolbox for analysis of singletrial EEG dynamics including independent component analysis”, Journal of Neuroscience Methods, 134:1 (2004), 9–21  crossref  mathscinet
11. Shell S., An introduction to Numpy and SciPy, http://www.engr.ucsb.edu/s̃hell/che210d/numpy.pdf, 2014 (data obrascheniya 26.11.2017)
12. Lee H.-C., DCCN Docker Swarm Cluster Documentation, https://media.readthedocs.org/pdf/dccn-docker-swarm/latest/dccn-docker-swarm.pdf, 2017 (data obrascheniya 26.11.2017)
13. De Souza J., Is Docker container based virtualization useful for Scientific purposes at DESY?, http://www.desy.de/f/students/2015/reports/JoshuaDeSouza.pdf.gz, University College London, 2015  zmath
14. Liu Z., Cho S., “Characterizing Machines and Workloads on a Google Cluster”, Proceedings of the Eighth International Workshop on Scheduling and Resource Management for Parallel and Distributed Systems, SRMPDS'12, 2012, 397–403
15. Gandhi V. A., Kumbharana C. K., “Comparative study of Amazon EC2 and Microsoft Azure cloud architecture”, International Journal of Advanced Networking Applications (IJANA), 2010, 117–123
16. Calatrava Arroyo A., High Performance Scientific Computing over Hybrid Cloud Platforms, Universitat Politecnica de Valencia, 2016  crossref
17. Ustinin M. N., Sychev V. V., Linas R. R., “Integrirovannyi paket programm MEGMRIAn dlya analiza i modelirovaniya dannykh magnitnoi entsefalografii”, Matematicheskaya biologiya i bioinformatika, 8:2 (2013), 691–707  mathnet  crossref  elib


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