Small-worldness favours network inference in synthetic neural networks
A main goal in the analysis of a complex system is to infer its underlying network structure from timeseries observations of its behaviour. The inference process is often done by using bi-variate similarity measures, such as the cross-correlation (CC) or mutual information (MI), however, the main fa...
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| Other Authors: | , , |
| Format: | article |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/20.500.12008/30874 |
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