Signal and noise extraction from analog memory elements for neuromorphic computing

The application of resistive and phase-change memories in neuromorphic computation will require efficient methods to quantify device-to-device and switching variability. Here, the authors assess the impact of a broad range of device switching mechanisms using machine learning regression techniques.

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Bibliographic Details
Main Authors: N. Gong, T. Idé, S. Kim, I. Boybat, A. Sebastian, V. Narayanan, T. Ando
Format: article
Language:EN
Published: Nature Portfolio 2018
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Online Access:https://doaj.org/article/a1f3b1e3f21e4dcd812626edb73f3983
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