基于异构结构的CdS-GeSe双模式记忆器,具有可调节的突触可塑性和用于神经形态硬件的混合信号切换
Girish U Kamble1, Somnath S Kundale2,3, Jun Sung Jang1
1Optoelectronics Convergence Research Center and Department of Materials Science and Engineering, Chonnam National University, Yongbong-Ro 77, Buk-Gu, Gwangju, 61186, Republic of Korea.
Small (Weinheim an der Bergstrasse, Germany)
|December 8, 2025
概括
这项研究介绍了用于神经形态计算的Ag/CdS-GeSe/FTO记忆器. 该设备在人工神经网络中的光学调制和图像识别方面显示出有希望的结果.
科学领域:
- 材料科学 材料科学 材料科学
- 神经科学是一个神经科学.
- 计算机科学 计算机科学
背景情况:
- 神经形态计算旨在模仿人类大脑的结构和功能.
- 记忆器是开发受大脑启发的计算系统的关键组件.
- 光学触发设备为信息处理提供了新的途径.
研究的目的:
- 为光学触发的神经形态应用开发和描述一个Ag/CdS-GeSe/FTO记忆器.
- 为了研究该设备的突触学习和内存存储的多功能功能.
- 用机器学习数据集评估memristor在图像识别任务中的性能.
主要方法:
- 一个Ag/CdS-GeSe/FTO记忆器装置的制造.
- 在电气和光学刺激 (405nm脉冲) 下的光电特性.
- 使用时尚-MNIST和数字MNIST数据集进行评估,以获得图像识别准确度.
主要成果:
- 电压变形后的memristor在±0.5V内显示了模拟到数字的转换和数字切换.
- 证明了突触功能,包括强化,抑郁,PPF和PPD.
- 在光电模式下实现75% (时尚-MNIST) 和95% (数字MNIST) 的图像识别准确度.
结论:
- Ag/CdS-GeSe/FTO记忆器显示了神经形态计算,机器学习和光学调制的潜力.
- 与电气模式相比,光电模式的操作提高了性能.
- 该设备为可靠的应用提供稳定的数据保留和出色的可重复性.
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