Polyoxometalate Accelerated Cationic Migration for Reservoir Computing-Reference-Cited by-同舟云学术

Polyoxometalate Accelerated Cationic Migration for Reservoir Computing

Published:2022-08-25 Issue:45 Volume:32 Page:2204721
ISSN:1616-301X
Container-title:Advanced Functional Materials
language:en
Short-container-title:Adv Funct Materials

Author:

Zhang Guohua¹^ORCID,Xiong Zi‐Yu²,Gong Yue²,Zhu Zexi³,Lv Ziyu²,Wang Yan⁴,Yang Jia‐Qin²,Xing Xuechao²,Wang Zhan‐Peng¹,Qin Jingrun²,Zhou Ye¹,Han Su‐Ting²^ORCID

Affiliation:

1. College of Civil and Transportation Engineering Institute for Advanced Study Shenzhen University Shenzhen 518060 P. R. China

2. College of Electronics and Information Engineering Shenzhen University Shenzhen 518060 P. R. China

3. State Key Laboratory of Supramolecular Structure and Materials College of Chemistry Jilin University Changchun 130012 P. R. China

4. School of Microelectronics Hefei University of Technology Hefei 230009 P. R. China

Publisher

Wiley

Subject

Electrochemistry,Condensed Matter Physics,Biomaterials,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adfm.202204721

Reference81 articles.

1. Multichannel parallel processing of neural signals in memristor arrays

2. Artificial neural networks in hardware: A survey of two decades of progress

3. Reservoir computing with biocompatible organic electrochemical networks for brain-inspired biosignal classification

4. Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach

5. Multilayer Reservoir Computing Based on Ferroelectric α‐In ₂ Se ₃ for Hierarchical Information Processing

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