Redox transistors for neuromorphic computing | Zendy

Elliot J. Fuller | Zendy; Yiyang Li | Zendy; Christopher Bennet | Zendy; Scott T. Keene | Zendy; Armantas Melianas | Zendy; Sapan Agarwal | Zendy; Mathhew J. Marinella | Zendy; Alberto Salleo | Zendy; A. Alec Talin | Zendy

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Redox transistors for neuromorphic computing

Author(s) -

Elliot J. Fuller,

Yiyang Li,

Christopher Bennet,

Scott T. Keene,

Armantas Melianas,

Sapan Agarwal,

Mathhew J. Marinella,

Alberto Salleo,

A. Alec Talin

Publication year - 2019

Publication title -

ibm journal of research and development

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.47

H-Index - 95

eISSN - 2151-8556

pISSN - 0018-8646

DOI - 10.1147/jrd.2019.2942285

Subject(s) - neuromorphic engineering , memristor , computer science , transistor , decoupling (probability) , electrochemical energy storage , cmos , computer architecture , nanotechnology , electronic engineering , artificial neural network , electrical engineering , materials science , voltage , engineering , artificial intelligence , electrochemistry , physics , control engineering , electrode , quantum mechanics , supercapacitor

Efficiency bottlenecks inherent to conventional computing in executing neural algorithms have spurred the development of novel devices capable of “in-memory” computing. Commonly known as “memristors,” a variety of device concepts including conducting bridge, vacancy filament, phase change, and other types have been proposed as promising elements in artificial neural networks for executing inferenc...

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