Spike-timing-dependent plasticity learning of coincidence detection with passively integrated memristive circuits
Hardware implementation of spiking neural networks holds promise for high energy efficient brain-inspired computing. Here, Prezioso et al. realize the detection of synchrony in a demo circuit composed of 20 metal-oxide memristor synapses connected to a leaky-integrate-and-fire silicon neuron.
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Autores principales: | M. Prezioso, M. R. Mahmoodi, F. Merrikh Bayat, H. Nili, H. Kim, A. Vincent, D. B. Strukov |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2018
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Materias: | |
Acceso en línea: | https://doaj.org/article/f5a2989a3d83440c9f152432cf481ea8 |
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