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Highly efficient ferroelectric capacitor reservoir computing through the study of its nonlinear polarization dynamics
Leisheng Jin,
Yiming Cao,
Zhuo Liu,
Tao Liu,
Lijie Li 
Physical Review E, Volume: 110, Issue: 4, Start page: 045307
Swansea University Author:
Lijie Li
Full text not available from this repository: check for access using links below.
DOI (Published version): 10.1103/PhysRevE.110.045307
Abstract
In this work, we aim to unveil the general correlations between the performance of a physical reservoir computing (RC) system and the inherent nonlinear dynamics of the adopted device. Taking the metal-ferroelectric-metal (MFM) capacitor, one of the most popular candidate devices for compute-in-memo...
| Published in: | Physical Review E |
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| ISSN: | 2470-0045 2470-0053 |
| Published: |
American Physical Society (APS)
2024
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa68443 |
| Abstract: |
In this work, we aim to unveil the general correlations between the performance of a physical reservoir computing (RC) system and the inherent nonlinear dynamics of the adopted device. Taking the metal-ferroelectric-metal (MFM) capacitor, one of the most popular candidate devices for compute-in-memory (CIM) technology, as the computational platform, we construct a nonlinear dynamical model of polarization in the ferroelectric layer. We then design the physical RC utilizing a single and/or an array of MFM capacitors by analyzing the model's stability and feasible dynamical cases. Subsequently, both the initial task and benchmark are numerically conducted to verify the designed RC's superiority. It is proven that by selecting an appropriate dynamical case, the RC can achieve a recognition rate as high as 96.13%, surpassing the results reported in previous work. Finally, we discuss how these key parameters play their role in the RC's performance from the perspective of affecting the system's transient responses, nonlinearity, and short-fading memory. This work paves the foundation for designing highly efficient reservoir computing based on MFM capacitors as well as other memristive devices such as memristors, tunneling diodes, etc. |
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| College: |
Faculty of Science and Engineering |
| Funders: |
The work was supported by the Research incubation fund (No. NY223091) from Nanjing University of Posts and Telecommunications. |
| Issue: |
4 |
| Start Page: |
045307 |