CuSe 记忆器驱动的神经形态架构:突触动力学,逻辑重新配置,以及无法克隆的双键加密应用
Xiang Zhang1, Lin Ge1, Hao Sun1
1Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou, China.
Small (Weinheim an der Bergstrasse, Germany)
|December 31, 2025
概括
本研究介绍了一种使用CuSe的新型突触记忆器,用于先进的神经形态计算和信息安全. 该设备可实现高效的逻辑操作和硬件级加密,克服传统计算的局限性.
科学领域:
- 材料科学 材料科学 材料科学
- 计算机工程 计算机工程
- 信息安全 信息安全
背景情况:
- 带有突触记忆元的神经形态计算为传统计算的局限性和信息安全挑战提供了解决方案.
- 探索基于memristor的新型电路对于超越传统电子设备的任务至关重要.
研究的目的:
- 开发和描述基于CuSe的突触记忆器,用于神经形态应用.
- 研究其在逻辑电路设计和信息安全加密方面的潜力.
主要方法:
- 制造Ag/CuSe/ITO的突触记忆器.
- 对突触行为,多级存储和可塑性模拟 (EPSC,LTP/LTD,PPF/PPD,STDP) 的评估.
- 实现逻辑操作 (AND,OR,NAND,NOR) 和双键加密系统.
主要成果:
- CuSe记忆器表现出高开关比率 (>10^3),优异的耐用性 (>10^4秒) 和低功耗 (~10^-8 J).
- 成功模拟了各种突触可塑性,并使用最小布尔基数实现了所有16个布尔运算.
- 开发一个双钥匙不可克隆的加密系统,用于硬件级加密/解密.
结论:
- CuSe突触记忆器显示出神经形态计算和信息安全应用的重大前景.
- 与逻辑电路的集成为先进的硬件安全性和非传统计算开辟了新的途径.
- 这项工作推进了基于memristor的解决方案,用于复杂的计算任务和安全的数据处理.
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