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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...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2023
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| Materias: | |
| 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 |