Affiliation:
1. Department of Electrical and Computer Engineering University of Mississippi Oxford MS USA
2. Department of Mechanical Engineering The Pennsylvania State University University Park PA USA
Abstract
Reservoir computing is a highly efficient machine learning framework for processing temporal data by extracting input features and mapping them into higher dimensional spaces. Physical reservoirs have been realized using spintronic oscillators, atomic switch networks, volatile memristors, etc. However, these devices are intrinsically energy‐dissipative due to their resistive nature, increasing their power consumption. Therefore, memcapacitive devices can provide a more energy‐efficient approach. Herein, volatile biomembrane‐based memcapacitors are leveraged as reservoirs to solve classification tasks and process time series in simulation and experimentally. This system achieves a 99.6% accuracy for spoken‐digit classification and a normalized mean square error of in a second‐order nonlinear regression task. Furthermore, to showcase the device's real‐time temporal data processing capability, a 100% accuracy for an epilepsy detection problem is achieved. Most importantly, it is demonstrated that each memcapacitor consumes an average of 41.5 fJ of energy per spike, regardless of the selected input voltage pulse width, while maintaining an average power of 415 fW for a pulse width of 100 ms, orders of magnitude lower than those achieved by state‐of‐the‐art devices. Lastly, it is believed that the biocompatible, soft nature of our memcapacitor renders it highly suitable for computing applications in biological environments.
Reference94 articles.
1. A.Graves A. r.Mohamed G.Hinton in2013 IEEE Int. Conf. Acoustics Speech and Signal Processing IEEE2013 pp.6645–6649.
2. H.Sak A.Senior K.Rao F.Beaufays arXiv preprint arXiv:1507.06947 2015.
3. T.Mikolov M.Karafiát L.Burget J.Černocký S.Khudanpur Interspeech Vol.2 Makuhari2010 pp.1045–1048.
4. S.Wiseman S. M.Shieber A. M.Rush inProc. of the 2018 Conf. on Empirical Methods in Natural Language Processing Association for Computational Linguistics Brussels Belgium2018 pp.3174–3187.
5. A. G.Salman B.Kanigoro Y.Heryadi inProc. 2015 Int. Conf. on Advanced Computer Science and Information Systems (ICACSIS 2015) IEEE Depok Indonesia2016 pp.281–285.
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