Energy-Efficient Hardware Implementation of Fully Connected Artificial Neural Networks Using Approximate Arithmetic Blocks

In this paper, we explore efficient hardware implementation of feedforward artificial neural networks (ANNs) using approximate adders and multipliers. Due to a large area requirement in a parallel architecture, the ANNs are implemented under the time-multiplexed architecture where computing resource...

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Detalles Bibliográficos
Autores principales: Esmali Nojehdeh, Mohammadreza, Altun, Mustafa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10123482/
https://www.ncbi.nlm.nih.gov/pubmed/37359149
http://dx.doi.org/10.1007/s00034-023-02363-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10123482/
https://www.ncbi.nlm.nih.gov/pubmed/37359149
http://dx.doi.org/10.1007/s00034-023-02363-w

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