Hybrid neuromorphic circuits exploiting non-conventional properties of RRAM for massively parallel local plasticity mechanisms
Recurrent neural networks are currently subject to intensive research efforts to solve temporal computing problems. Neuromorphic processors (NPs), composed of networked neuron and synapse circuit models, natively compute in time and offer an ultralow power solution particularly suited to emerging te...
Main Authors: | Thomas Dalgaty, Melika Payvand, Filippo Moro, Denys R. B. Ly, Florian Pebay-Peyroula, Jerome Casas, Giacomo Indiveri, Elisa Vianello |
---|---|
Format: | Article |
Language: | English |
Published: |
AIP Publishing LLC
2019-08-01
|
Series: | APL Materials |
Online Access: | http://dx.doi.org/10.1063/1.5108663 |
Similar Items
-
Mosaic: in-memory computing and routing for small-world spike-based neuromorphic systems
by: Thomas Dalgaty, et al.
Published: (2024-01-01) -
Author Correction: Self-organization of an inhomogeneous memristive hardware for sequence learning
by: Melika Payvand, et al.
Published: (2022-10-01) -
Self-organization of an inhomogeneous memristive hardware for sequence learning
by: Melika Payvand, et al.
Published: (2022-10-01) -
Neuromorphic object localization using resistive memories and ultrasonic transducers
by: Filippo Moro, et al.
Published: (2022-06-01) -
Oxide-based RRAM materials for neuromorphic computing
by: Hong, XiaoLiang, et al.
Published: (2020)