التفاصيل البيبلوغرافية
| العنوان: |
Gesture recognition with Brownian reservoir computing using geometrically confined skyrmion dynamics |
| المؤلفون: |
Beneke, Grischa, Winkler, Thomas Brian, Raab, Klaus, Brems, Maarten A., Kammerbauer, Fabian, Gerhards, Pascal, Knobloch, Klaus, Mentink, Johan, Kläui, Mathias |
| سنة النشر: |
2024 |
| المجموعة: |
Condensed Matter |
| مصطلحات موضوعية: |
Condensed Matter - Materials Science |
| الوصف: |
Physical reservoir computing (RC) is a beyond von-Neumann computing paradigm that harnesses the dynamical properties of a complex physical system (reservoir) to process information efficiently in tasks such as pattern recognition. This hardware-centered approach drastically reduces training efforts and holds potential for significantly reduced energy consumption operation. Magnetic skyrmions, topological, particle-like spin textures, are considered highly promising candidates for reservoir computing systems due to their non-linear interactions and established mechanisms for low power manipulation combined with thermally excited dynamics. So far spin-based reservoir computing has been used for static detection or has been based on intrinsic magnetization dynamics timescales, that require cumbersome rescaling of typically slower real-world data. Here we harness the power of time-multiplexed skyrmion RC by adjusting the intrinsic timescales of the reservoir to the timescales of real-world temporal patterns: we recognize hand gestures recorded with range-doppler radar on a millisecond timescale and feed the data as a time-dependent voltage excitation directly into our device. We observe the temporal evolution of the skyrmion trajectory using read-out at just one position of the reservoir, which allows for scaling onto the nanometer scale. We find that our hardware solution exhibits competitive performance compared with a state-of-the-art energy-intensive software-based neural network. The key advantage of our hardware approach lies in its capacity to seamlessly integrate data from sensors without the need for temporal conversion, thanks to the time-dependent input and tunable intrinsic timescales of the skyrmion dynamics in the reservoir. This feature enables real-time feeding of the reservoir, opening a multitude of applications. |
| نوع الوثيقة: |
Working Paper |
| URL الوصول: |
http://arxiv.org/abs/2403.01877 |
| رقم الانضمام: |
edsarx.2403.01877 |
| قاعدة البيانات: |
arXiv |