Emulating complex networks with a single delay differential equation
European Physical Journal: Special Topics, ISSN: 1951-6401, Vol: 230, Issue: 14-15, Page: 2865-2874
2021
- 4Citations
- 10Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
A single dynamical system with time-delayed feedback can emulate networks. This property of delay systems made them extremely useful tools for Machine-Learning applications. Here, we describe several possible setups, which allow emulating multilayer (deep) feed-forward networks as well as recurrent networks of coupled discrete maps with arbitrary adjacency matrix by a single system with delayed feedback. While the network’s size can be arbitrary, the generating delay system can have a low number of variables, including a scalar case.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85107459857&origin=inward; http://dx.doi.org/10.1140/epjs/s11734-021-00162-5; https://link.springer.com/10.1140/epjs/s11734-021-00162-5; https://dx.doi.org/10.1140/epjs/s11734-021-00162-5; https://link.springer.com/article/10.1140/epjs/s11734-021-00162-5
Springer Science and Business Media LLC
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