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A Circuit-Based Neural Network with Hybrid Learning of Backpropagation and Random Weight Change Algorithms
A hybrid learning method of a software-based backpropagation learning and a hardware-based RWC learning is proposed for the development of circuit-based neural networks. The backpropagation is known as one of the most efficient learning algorithms. A weak point is that its hardware implementation is...
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| Publicado no: | Sensors (Basel) |
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| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5298589/ https://ncbi.nlm.nih.gov/pubmed/28025566 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s17010016 |
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