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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5298589/ https://www.ncbi.nlm.nih.gov/pubmed/28025566 http://dx.doi.org/10.3390/s17010016 |