Local active memristive oscillator enables controllable complex behaviours and frequency domain extraction

Physical non-linearities near the Mott transition exhibit substantial potential for neuromorphic computing. The complex computational behaviour stems from their intrinsic local active characteristics. Most studies focus on decay dynamics or regular oscillations, treating Mott devices primarily as simple threshold elements. Challenges remain in connecting measurable material properties to more complex device dynamics and their control methods through a unified theoretical model. Here, we develop a thermodynamic compact model for vanadium oxide devices based on electrical measurements and the local active principle. Utilizing the non-linearities near the Mott transition, we propose an injection-based control method to regulate behaviours of non-linear oscillators, such as frequency division, stochastic oscillations and frequency locking. Finally, a single device operating at the edge of chaos demonstrates exceptional capability in extracting information in the frequency domain within a physical computing framework, achieving performance equivalent to a two-layer convolutional neural network on the same task. This work facilitates a paradigm shift from traditional local passive devices to local active devices, bridging the physical non-linearities, circuit dynamics and computational theory to advance dynamic neuromorphic computing.

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Publication Details

Journal
National Science Review
Published
2025-12-05
DOI
https://doi.org/10.1093/nsr/nwaf546
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
0.00

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article

Local active memristive oscillator enables controllable complex behaviours and frequency domain extraction

Yuchao Yang, Yaoyu Tao, Pek Jun Tiw, Ye Liu et al.
National Science Review
Neural Networks and Reservoir Computing
article

Local active memristive oscillator enables controllable complex behaviours and frequency domain extraction

Yuchao Yang, Yaoyu Tao, Pek Jun Tiw, Ye Liu, Teng Zhang, Yanghao Wang
article en

Abstract

Physical non-linearities near the Mott transition exhibit substantial potential for neuromorphic computing. The complex computational behaviour stems from their intrinsic local active characteristics. Most studies focus on decay dynamics or regular oscillations, treating Mott devices primarily as simple threshold elements. Challenges remain in connecting measurable material properties to more complex device dynamics and their control methods through a unified theoretical model. Here, we develop a thermodynamic compact model for vanadium oxide devices based on electrical measurements and the local active principle. Utilizing the non-linearities near the Mott transition, we propose an injection-based control method to regulate behaviours of non-linear oscillators, such as frequency division, stochastic oscillations and frequency locking. Finally, a single device operating at the edge of chaos demonstrates exceptional capability in extracting information in the frequency domain within a physical computing framework, achieving performance equivalent to a two-layer convolutional neural network on the same task. This work facilitates a paradigm shift from traditional local passive devices to local active devices, bridging the physical non-linearities, circuit dynamics and computational theory to advance dynamic neuromorphic computing.

National Science ReviewVol. 13(2)
Peking University (CN), Beijing Academy of Artificial Intelligence (CN), Chinese Institute for Brain Research (CN), Fraunhofer Institute for Integrated Circuits (DE), Peking University Shenzhen Hospital (CN), Shanghai Center for Brain Science and Brain-Inspired Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 79%
Neural Networks and Reservoir Computing
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