Please use this identifier to cite or link to this item: 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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