
Dataset and codes required to reproduce the noise analysis of complex- & real-valued neural networks, as described in the article "Role of all-optical neural-networks" (https://doi.org/10.1103/PhysRevApplied.21.014028) Codes in python require the use of cvnn library published by J. Agustin Barrachina at https://github.com/NEGU93/cvnn/tree/v2.0 (URL) We acknowledge support from the National Science Center, Poland under Grants No. 2019/35/N/ST3/01379, No. 2020/37/B/ST3/01657, and No. 2021/43/B/ST3/00752, and the Foundation for Polish Science (FNP).
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
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| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
