Protonic All-Solid-State Electrochemical Device as an Artificial Synapse for CMOS-Compatible Neuromorphic Computing
The development of artificial intelligence (AI) has changed the overall landscape of information technology.[1] However, conventional computing hardware is energetically unfavorable to handle multifarious AI tasks because the frequent data transfer between the physically separated microprocessors an...
Main Author: | Ryu, Seungchan |
---|---|
Other Authors: | Li, Ju |
Format: | Thesis |
Published: |
Massachusetts Institute of Technology
2023
|
Online Access: | https://hdl.handle.net/1721.1/152130 |
Similar Items
-
CMOS-compatible neuromorphic devices for neuromorphic perception and computing: a review
by: Yixin Zhu, et al.
Published: (2023-01-01) -
CMOS-Compatible Memristor for Optoelectronic Neuromorphic Computing
by: Facai Wu, et al.
Published: (2022-11-01) -
Protonic solid-state electrochemical synapse for physical neural networks
by: Yao, Xiahui, et al.
Published: (2021) -
An Interface‐Type Memristive Device for Artificial Synapse and Neuromorphic Computing
by: Sundar Kunwar, et al.
Published: (2023-08-01) -
Memristive Artificial Synapses for Neuromorphic Computing
by: Wen Huang, et al.
Published: (2021-03-01)