在和激发下对memristors的行为建模
Elena Solovyeva1, Artyom Serdyuk1
1Department of Electrical Engineering Theory, Saint Petersburg Electrotechnical University "LETI", 197022 St. Petersburg, Russia.
Micromachines
|January 23, 2024
概括
行为建模简化了memristor分析. 零碎神经模型对memristor (第四个被动电元素) 传输特征的准确性高于多项式模型.
科学领域:
- 纳米系统工程 纳米系统工程
- 电气工程 电气工程
- 计算建模 计算建模
背景情况:
- 记忆器是第四个被动电气元件,由于不同的实现技术,在分析建模中存在挑战.
- 使用输入-输出关系的行为建模为memristor表征提供了一个可行的替代方案.
研究的目的:
- 提出一种方法来简化memristors的行为模型,特别是在和输入信号下.
- 开发和比较memristor传输特征的部位神经和多项式模型.
主要方法:
- 利用延迟线从和输入中形成分割信号,最小化简化行为模型的信号数量.
- 构建零碎的神经和多项式模型来近似memristor的转移特征,当前动态由伯努利微分方程控制.
主要成果:
- 提议的延迟线方法通过减少分割信号的数量,有效地简化了行为建模.
- 部分神经模型和多项式模型都成功开发,以捕捉memristor动态.
- 在相似的复杂度水平上,零碎神经模型与零碎多项式模型相比,显示出更高的准确性.
结论:
- 行为建模,特别是简化信号处理,对于描述复杂的memristor设备至关重要.
- 零碎神经网络为memristor建模提供了比零碎多项式方法更准确的方法,在纳米系统中提供了更好的性能.
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