蜘蛛
扰动(地质)
神经形态工程学
纳米技术
记忆电阻器
计算机科学
材料科学
工程类
电子工程
人工智能
生态学
生物
古生物学
人工神经网络
作者
Wenbo Sun,Y. M. Li,Christy Giji Jenson,Sharif Md. Sadaf,Qiang Yu,Yiwen Zhang,Xinjun Liu
摘要
This article introduces a memristor-coupled oscillatory network utilizing niobium dioxide (NbO2) memristors and a biomimetic spider web structure. It focuses on the dynamic behaviors of single oscillators and small-scale networks within this unique system, particularly emphasizing voltage, current, and frequency characteristics. By strategically applying step voltage signals on a 1 + 3 node single-layer bio-inspired spider network, a single disturbance or multiple disturbances were addressed under continuous external stimuli, with analyzing phase differences induced by disturbances at various locations within the network and systematically categorizing these phases to empower decision-making. These pattern differences enable precise location-resolved disturbance detection through eight encodable phase patterns and their corresponding phase-space trajectories, showcasing memristors' precision in dynamic control. Additionally, amplitude changes and phase relationships between oscillators can be visually represented through color-mapped voltage values. This work opens avenues for developing intelligent, adaptive systems, advancing neuromorphic computing, and intelligent system control, offering possibilities for artificial intelligence to process complex information.
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