DSpace Repository

Hardware implementation of Hopfield-like neural networks: Quantitative analysis of FPGA approach

Show simple item record

dc.contributor.author ZAPOROJAN, Sergiu
dc.contributor.author CARBUNE, Viorel
dc.contributor.author SLAVESCU, Radu Razvan
dc.date.accessioned 2022-04-26T06:08:11Z
dc.date.available 2022-04-26T06:08:11Z
dc.date.issued 2021
dc.identifier.citation ZAPOROJAN, Sergiu, CARBUNE, Viorel, SLAVESCU, Radu Razvan. Hardware implementation of Hopfield-like neural networks: Quantitative analysis of FPGA approach. In: 17th International Conference on Intelligent Computer Communication and Processing: proc. IEEE ICCP., 28-30 Oct. 2021. 2021, Cluj-Napoca, Romania, 2021, pp. 243-250. ISBN 978-1-6654-0976-6. en_US
dc.identifier.isbn 978-1-6654-0976-6
dc.identifier.uri https://doi.org/10.1109/ICCP53602.2021.9733628
dc.identifier.uri http://repository.utm.md/handle/5014/20217
dc.description Acces full text - https://doi.org/10.1109/ICCP53602.2021.9733628 en_US
dc.description.abstract This paper provides a rigorous analysis of FPGA implementation of Hopfield-like neural networks. The relationship between the hardware resources used to synthesize the data path and those used to provide network connections is discussed, as well as the distribution of these resources and how it depends on the variation in the architectural parameters of the network. The analysis presented in this paper is based on Intel/Altera Cyclone FPGA devices. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject machine learning en_US
dc.subject Hopfield neural networks en_US
dc.subject neural networks en_US
dc.subject analytical models en_US
dc.subject hardware en_US
dc.subject embedded intelligence en_US
dc.title Hardware implementation of Hopfield-like neural networks: Quantitative analysis of FPGA approach en_US
dc.type Article en_US


Files in this item

The following license files are associated with this item:

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivs 3.0 United States Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States

Search DSpace


Advanced Search

Browse

My Account