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Published in 2020 at "Journal of neural engineering"
DOI: 10.1088/1741-2552/abb5bd
Abstract: OBJECTIVE When developing approaches for automatic preprocessing of electroencephalogram (EEG) signals in non-isolated demanding environment such as intensive care unit (ICU) or even outdoor environment, one of the major concerns is varying nature of characteristics…
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Keywords:
correlation driven;
driven mapping;
deep learning;
correlation ... See more keywords
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Published in 2019 at "Physical review. E"
DOI: 10.1103/physreve.99.053310
Abstract: Multiple-point geostatistics (MPS) is a competitive algorithm that produces a set of geologically realistic models. Viewing a training image (TI) as a prior model, MPS extracts patterns from the TI and reproduces patterns which are…
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Keywords:
evaluation;
training image;
correlation driven;
simulation ... See more keywords
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Published in 2021 at "IEEE Transactions on Smart Grid"
DOI: 10.1109/tsg.2020.3032716
Abstract: Robust optimization (RO) has been a proficient approach for uncertainty dispatch in microgrids. In view of the strong conservativeness of traditional RO models, this article proposes a historical-correlation-driven (HCD) RO method for the MG dispatch…
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Keywords:
optimization;
historical correlation;
correlation driven;
approach ... See more keywords
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Published in 2023 at "Materials"
DOI: 10.3390/ma16041649
Abstract: The appearance of intrinsic ferromagnetism in 2D materials opens the possibility of investigating the interplay between magnetism and topology. The magnetic anisotropy energy (MAE) describing the easy axis for magnetization in a particular direction is…
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Keywords:
topology;
correlation driven;
topological transition;
transition janus ... See more keywords