We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
High-order sensory processing nanocircuit based on coupled VO<sub>2</sub> oscillators.
- Authors
Yang, Ke; Wang, Yanghao; Tiw, Pek Jun; Wang, Chaoming; Zou, Xiaolong; Yuan, Rui; Liu, Chang; Li, Ge; Ge, Chen; Wu, Si; Zhang, Teng; Huang, Ru; Yang, Yuchao
- Abstract
Conventional circuit elements are constrained by limitations in area and power efficiency at processing physical signals. Recently, researchers have delved into high-order dynamics and coupled oscillation dynamics utilizing Mott devices, revealing potent nonlinear computing capabilities. However, the intricate yet manageable population dynamics of multiple artificial sensory neurons with spatiotemporal coupling remain unexplored. Here, we present an experimental hardware demonstration featuring a capacitance-coupled VO2 phase-change oscillatory network. This network serves as a continuous-time dynamic system for sensory pre-processing and encodes information in phase differences. Besides, a decision-making module for special post-processing through software simulation is designed to complete a bio-inspired dynamic sensory system. Our experiments provide compelling evidence that this transistor-free coupling network excels in sensory processing tasks such as touch recognition and gesture recognition, achieving significant advantages of fewer devices and lower energy-delay-product compared to conventional methods. This work paves the way towards an efficient and compact neuromorphic sensory system based on nano-scale nonlinear dynamics. It is challenging to create efficient and compact neuromorphic sensory system based on nano-scale nonlinear dynamics. Yang et al. present a capacitance-coupled VO2 oscillatory network, which serves as a continuous-time dynamic system for sensory pre-processing, enabling tasks such as touch and gesture recognition.
- Subjects
SENSORIMOTOR integration; NONLINEAR oscillators; DYNAMICAL systems; CIRCUIT elements; SENSORY neurons; SIGNAL processing; BIOLOGICALLY inspired computing
- Publication
Nature Communications, 2024, Vol 15, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-024-45992-8