← 返回
基于TaOx的双功能忆阻器用于紧凑型漏泄积分-放电神经元
TaOx-based bifunctional memristor for compact leaky integrate-and-fire neuron
| 作者 | Lijuan Cao · Yunhao Luo · Xiaomin Cheng · Xiangshui Miao |
| 期刊 | Applied Physics Letters |
| 出版日期 | 2025年1月 |
| 卷/期 | 第 127 卷 第 4 期 |
| 技术分类 | 储能系统技术 |
| 技术标签 | 储能系统 |
| 相关度评分 | ★★★★ 4.0 / 5.0 |
| 关键词 | 人工智能 人工神经元 双功能忆阻器 泄漏积分触发神经元 神经形态计算 |
语言:
中文摘要
随着人工智能的快速发展,人工神经元作为关键组件受到广泛关注。然而,现有电路结构复杂,不利于高密度集成。本文提出一种Ag/Ti/TaOx/Pt双功能忆阻器,在不同电压偏置下表现出动态与阈值开关特性。利用该特性,将两个器件背对背连接,构建了漏泄积分-放电(LIF)神经元,仅需一步光刻即可实现高度紧凑的神经元结构。电学测试验证了其LIF功能及对输入信号的适应性,为神经形态计算提供了新型双功能器件与紧凑型人工神经元方案。
English Abstract
With the rapid development of artificial intelligence, artificial neurons have received increasing attention as essential components. However, the complexity of existing artificial neuron circuits is adverse to high integration applications due to their complex configuration. Here, we propose a bifunctional memristor, Ag/Ti/TaOx/Pt, which exhibits dynamic and threshold switching performance with different voltage biases. Utilizing these properties, we connected two Ag/Ti/TaOx/Pt devices in a back-to-back configuration to form a leaky integrate-and-fire (LIF) neuron. Moreover, only a one-step lithography process is required to realize a compact neuron with LIF functions. The electrical tests of the artificial neurons were carried out to verify their ability to execute the LIF function and their adaptability to input signals. This work provides a bifunctional device and a highly compact artificial neuron for neuromorphic computing.
S
SunView 深度解读
该TaOx双功能忆阻器的紧凑型神经元技术对阳光电源智能控制系统具有前瞻性价值。其漏泄积分-放电特性可应用于:1)PowerTitan储能系统的电池管理,通过神经形态计算实现高密度集成的SOC/SOH预测算法,提升BMS智能化水平;2)iSolarCloud平台的边缘计算节点,利用忆阻器低功耗特性实现本地化故障诊断与预测性维护;3)构网型GFM控制器的自适应算法优化,通过类脑计算加速复杂工况下的实时响应。该技术的高集成度与低功耗特性为阳光电源开发下一代智能化、轻量化控制芯片提供了新思路,有助于降低系统成本并提升边缘智能处理能力。