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All-ferroelectric implementation of reservoir computing

Reservoir computing (RC) offers efficient temporal information processing with low training cost. All-ferroelectric implementation of RC is appealing because it can fully exploit the merits of ferroelectric memristors (e.g., good controllability); however, this has been undemonstrated due to the cha...

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Detalles Bibliográficos
Autores principales: Chen, Zhiwei, Li, Wenjie, Fan, Zhen, Dong, Shuai, Chen, Yihong, Qin, Minghui, Zeng, Min, Lu, Xubing, Zhou, Guofu, Gao, Xingsen, Liu, Jun-Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10275999/
https://www.ncbi.nlm.nih.gov/pubmed/37328514
http://dx.doi.org/10.1038/s41467-023-39371-y
Descripción
Sumario:Reservoir computing (RC) offers efficient temporal information processing with low training cost. All-ferroelectric implementation of RC is appealing because it can fully exploit the merits of ferroelectric memristors (e.g., good controllability); however, this has been undemonstrated due to the challenge of developing ferroelectric memristors with distinctly different switching characteristics specific to the reservoir and readout network. Here, we experimentally demonstrate an all-ferroelectric RC system whose reservoir and readout network are implemented with volatile and nonvolatile ferroelectric diodes (FDs), respectively. The volatile and nonvolatile FDs are derived from the same Pt/BiFeO(3)/SrRuO(3) structure via the manipulation of an imprint field (E(imp)). It is shown that the volatile FD with E(imp) exhibits short-term memory and nonlinearity while the nonvolatile FD with negligible E(imp) displays long-term potentiation/depression, fulfilling the functional requirements of the reservoir and readout network, respectively. Hence, the all-ferroelectric RC system is competent for handling various temporal tasks. In particular, it achieves an ultralow normalized root mean square error of 0.017 in the Hénon map time-series prediction. Besides, both the volatile and nonvolatile FDs demonstrate long-term stability in ambient air, high endurance, and low power consumption, promising the all-ferroelectric RC system as a reliable and low-power neuromorphic hardware for temporal information processing.