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A Review on Multi-Level Asymmetric Design for 2D Neuromorphic Devices. [PDF]

open access: yesNanomicro Lett
Sun Y   +5 more
europepmc   +1 more source

Spintronics for Neuromorphic Engineering

2021
Today’s machine learning and artificial neural networks rely heavily on conventional electronic circuits. Progress in machine learning models and algorithms will eventually be limited by issues such as high power dissipation and scaling challenges posed by CMOS, and it is necessary to resolve these through a bottom-up approach.
Gerard Joseph Lim   +2 more
openaire   +1 more source

Third-Order Nanocircuit Elements for Neuromorphic Engineering

Nature, 2020
Current hardware approaches to biomimetic or neuromorphic artificial intelligence rely on elaborate transistor circuits to simulate biological functions. However, these can instead be more faithfully emulated by higher-order circuit elements that naturally express neuromorphic nonlinear dynamics1-4.
Suhas Kumar   +2 more
exaly   +3 more sources

Neuromorphic Engineering

2021
The brain is not a glorified digital computer. It does not store information in registers, and it does not mathematically transform mental representations to establish perception or behavior. The brain cannot be downloaded to a computer to provide immortality, nor can it destroy the world by having its emerged consciousness traveling in cyberspace ...
openaire   +1 more source

Dielectric Engineered Two-Dimensional Neuromorphic Transistors

Nano Letters, 2021
Two-dimensional (2D) materials, which exhibit planar-wafer technique compatibility and pure electrically triggered communication, have established themselves as potential candidates in neuromorphic architecture integration. However, the current 2D artificial synapses are mainly realized at a single-device level, where the development of 2D scalable ...
Du Xiang   +4 more
openaire   +2 more sources

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