May 14, 2024, 4:43 a.m. | Nadezhda Semenova

cs.LG updates on arXiv.org arxiv.org

arXiv:2405.07670v1 Announce Type: cross
Abstract: In recent years, more and more works have appeared devoted to the analog (hardware) implementation of artificial neural networks, in which neurons and the connection between them are based not on computer calculations, but on physical principles. Such networks offer improved energy efficiency and, in some cases, scalability, but may be susceptible to internal noise. This paper studies the influence of noise on the functioning of recurrent networks using the example of trained echo state …

abstract analog artificial artificial neural networks arxiv computer cs.lg cs.ne echo efficiency energy energy efficiency hardware impact implementation networks neural networks neurons noise state them type

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