OscNet: Machine Learning on CMOS Oscillator Networks

In this brief, we propose a pipeline for machine learning on CMOS Oscillator Networks (OscNet), inspired by human visual system development. By relying solely on forward propagation, OscNet is energy efficient and preserves biological plausibility. Our simulations confirm the effectiveness of the proposed architectures, and experimental results demonstrate that the Hebbian-learning pipeline on OscNet matches traditional machine learning algorithms, underscoring its promise as an energy efficient and high performance new computational paradigm. The repository for OscNet family is: https://github.com/RussRobin/OscNet.