A biomimetic neural encoder for spiking neural network
The implementation of spiking neural network in future neuromorphic hardware requires hardware encoder analogous to the sensory neurons. The authors show a biomimetic dual-gated MoS2 field effect transistor capable of encoding analog signals into stochastic spike trains at energy cost of 1–5 pJ/spik...
Main Authors: | Shiva Subbulakshmi Radhakrishnan, Amritanand Sebastian, Aaryan Oberoi, Sarbashis Das, Saptarshi Das |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2021-04-01
|
Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-021-22332-8 |
Similar Items
-
A biomimetic 2D transistor for audiomorphic computing
by: Sarbashis Das, et al.
Published: (2019-08-01) -
Neural encoding with unsupervised spiking convolutional neural network
by: Chong Wang, et al.
Published: (2023-08-01) -
Graphene memristive synapses for high precision neuromorphic computing
by: Thomas F. Schranghamer, et al.
Published: (2020-10-01) -
On-Chip Trainable Spiking Neural Networks Using Time-To-First-Spike Encoding
by: Jiseong Im, et al.
Published: (2022-01-01) -
Information Encoding in Bursting Spiking Neural Network Modulated by Astrocytes
by: Sergey V. Stasenko, et al.
Published: (2023-05-01)