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https://hdl.handle.net/10356/143405
Title: | A neuromorphic device implemented on a salmon-DNA electrolyte and its application to artificial neural networks | Authors: | Kang, Dong-Ho Kim, Jeong-Hoon Oh, Seyong Park, Hyung-Youl Dugasani, Sreekantha Reddy Kang, Beom-Seok Choi, Changhwan Choi, Rino Lee, Sungjoo Park, Sung Ha Heo, Keun Park, Jin-Hong |
Keywords: | Engineering::Electrical and electronic engineering | Issue Date: | 2019 | Source: | Kang, D.-H., Kim, J.-H., Oh, S., Park, H.-Y., Dugasani, S. R., Kang, B.-S., ... Park, J.-H. (2019). A neuromorphic device implemented on a salmon-DNA electrolyte and its application to artificial neural networks. Advanced Science, 6(17), 1901265-. doi:10.1002/advs.201901265 | Journal: | Advanced Science | Abstract: | A bioinspired neuromorphic device operating as synapse and neuron simultaneously, which is fabricated on an electrolyte based on Cu2+-doped salmon deoxyribonucleic acid (S-DNA) is reported. Owing to the slow Cu2+ diffusion through the base pairing sites in the S-DNA electrolyte, the synaptic operation of the S-DNA device features special long-term plasticity with negative and positive nonlinearity values for potentiation and depression (αp and αd), respectively, which consequently improves the learning/recognition efficiency of S-DNA-based neural networks. Furthermore, the representative neuronal operation, "integrate-and-fire," is successfully emulated in this device by adjusting the duration time of the input voltage stimulus. In particular, by applying a Cu2+ doping technique to the S-DNA neuromorphic device, the characteristics for synaptic weight updating are enhanced (|αp|: 31→20, |αd|: 11→18, weight update margin: 33→287 nS) and also the threshold conditions for neuronal firing (amplitude and number of stimulus pulses) are modulated. The improved synaptic characteristics consequently increase the Modified National Institute of Standards and Technology (MNIST) pattern recognition rate from 38% to 44% (single-layer perceptron model) and from 89.42% to 91.61% (multilayer perceptron model). This neuromorphic device technology based on S-DNA is expected to contribute to the successful implementation of a future neuromorphic system that simultaneously satisfies high integration density and remarkable recognition accuracy. | URI: | https://hdl.handle.net/10356/143405 | ISSN: | 2198-3844 | DOI: | 10.1002/advs.201901265 | Schools: | School of Electrical and Electronic Engineering | Rights: | © 2019 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and repro-duction in any medium, provided the original work is properly cited. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Journal Articles |
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