Biomemristor Reservoir Computing With Multi-Value Mask for Improving Recognition Performance-Reference-Cited by-同舟云学术

Biomemristor Reservoir Computing With Multi-Value Mask for Improving Recognition Performance

Published:2024-09 Issue:9 Volume:45 Page:1657-1660
ISSN:0741-3106
Container-title:IEEE Electron Device Letters
language:
Short-container-title:IEEE Electron Device Lett.

Author:

Li Yang¹,Cao Jie²^ORCID,Yu Jie²,Liu Mengyang²,Zhang Xumeng²^ORCID,Chen Jiewen²,Xu Qian²,Liu Xusheng²,Qiu Jie²^ORCID,Chen Yan²,Li Mingxun²,Zhu Chenxin³,Xu Zhongguang³,Ma Xiaohua⁴^ORCID,Wang Hong⁴^ORCID,Wang Ming²^ORCID

Affiliation:

1. Hangzhou Institute of Technology and the School of Advanced Materials and Nanotechnology, Xidian University, Xi’an, China

2. Frontier Institute of Chip and System, State Key Laboratory of Integrated Chips and Systems, Fudan University, Shanghai, China

3. School of Microelectronics, University of Science and Technology of China, Hefei, China

4. State Key Laboratory of Wide Bandgap Semiconductor Devices and Integrated Technology, School of Microelectronics, Xidian University, Xi’an, China

Funder

National Key Research and Development Program of China

Concept Foundation of Hangzhou Institute of Technology, Xidian University

National Natural Science Foundation of China

Shanghai Pujiang Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/55/10648890/10589373.pdf?arnumber=10589373

Reference27 articles.

1. Information processing using a single dynamical node as complex system

2. Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations

3. Simulation platform for pattern recognition based on reservoir computing with memristor networks

4. Experimental demonstration of reservoir computing on a silicon photonics chip

5. Neuromorphic computing with nanoscale spintronic oscillators