Silicon Nanowire Charge Trapping Memory for Energy-Efficient Neuromorphic Computing-Reference-Cited by-同舟云学术

Silicon Nanowire Charge Trapping Memory for Energy-Efficient Neuromorphic Computing

Published:2023 Issue: Volume:22 Page:409-416
ISSN:1536-125X
Container-title:IEEE Transactions on Nanotechnology
language:
Short-container-title:IEEE Trans. Nanotechnology

Author:

Ansari Md. Hasan Raza¹,Kannan Udaya Mohanan²^ORCID,El-Atab Nazek¹^ORCID

Affiliation:

1. SAMA Labs, Division of Computer, Electrical and Mathematical Science and Engineering Division, Electrical and Computer Engineering, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

2. Department of Electronic Engineering, Gachon University, Seongnam, South Korea

Funder

King Abdullah University of Science and Technology Baseline Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications

Link

http://xplorestaging.ieee.org/ielx7/7729/10016255/10186234.pdf?arnumber=10186234

Reference43 articles.

1. 3-D Stacked Synapse Array Based on Charge-Trap Flash Memory for Implementation of Deep Neural Networks

2. Short-Term Memory to Long-Term Memory Transition Mimicked in IZO Homojunction Synaptic Transistors

3. Emulation of synaptic functions with low voltage organic memtransistor for hardware oriented neuromorphic computing

4. MoS2-based Charge-trapping synaptic device with electrical and optical modulated conductance

5. D.O. Hebb: The Organization of Behavior, Wiley: New York; 1949

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