Bidirectional Non-Filamentary RRAM as an Analog Neuromorphic Synapse, Part II: Impact of Al/Mo/Pr<sub>0.7</sub>Ca<sub>0.3</sub>MnO<sub>3</sub> Device Characteristics on Neural Network Training Accuracy
Neuromorphic computing embraces the “device history” offered by many analog non-volatile memory (NVM) devices to implement the small weight changes computed by a gradient-descent learning algorithm such as backpropagation. Deterministic and stochastic imperfections in the condu...
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Autores principales: | , , , , , , , , |
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Formato: | article |
Lenguaje: | EN |
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IEEE
2018
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Acceso en línea: | https://doaj.org/article/36efdf8a930c4875b9b68848f34662b6 |
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