Journal of Semiconductors, Volume. 42, Issue 6, 064101(2021)
Oscillation neuron based on a low-variability threshold switching device for high-performance neuromorphic computing
[1] G Indiveri, B Linares-Barranco, R Legenstein et al. Integration of nanoscale memristor synapses in neuromorphic computing architectures. Nanotechnology, 24, 384010(2013).
[2] S Ambrogio, S Balatti, V Milo et al. Neuromorphic learning and recognition with one-transistor-one-resistor synapses and bistable metal oxide RRAM. IEEE Trans Electron Devices, 63, 1508(2016).
[3] G W Burr, R M Shelby, A Sebastian et al. Neuromorphic computing using non-volatile memory. Adv Phys X, 2, 89(2017).
[4] M A Zidan, J P Strachan, W D Lu. The future of electronics based on memristive systems. Nat Electron, 1, 22(2018).
[5] B F Merrikh, M Prezioso, B Chakrabarti et al. Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits. Nat Commun, 9, 2331(2017).
[6] P Yao, H Q Wu, B Gao et al. Fully hardware-implemented memristor convolutional neural network. Nature, 577, 641(2020).
[7] S Choi, J Yang, G Wang. Emerging memristive artificial synapses and neurons for energy-efficient neuromorphic computing. Adv Mater, 32, 2004659(2020).
[8] J D Zhu, T Zhang, Y C Yang et al. A comprehensive review on emerging artificial neuromorphic devices. Appl Phys Rev, 7, 011312(2020).
[9] D Kadetotad, Z H Xu, A Mohanty et al. Parallel architecture with resistive crosspoint array for dictionary learning acceleration. IEEE J Emerg Sel Top Circuits Syst, 5, 194(2015).
[10] Q L Hua, H Q Wu, B Gao et al. Low-voltage oscillatory neurons for memristor-based neuromorphic systems. Glob Challenges, 3, 1900015(2019).
[11] B J Dang, K Q Liu, J D Zhu et al. Stochastic neuron based on IGZO Schottky diodes for neuromorphic computing. APL Mater, 7, 071114(2019).
[12] S Li, X J Liu, S K Nandi et al. High-endurance MHz electrical self-oscillation in Ti/NbO
[13] L G Gao, P Y Chen, S M Yu. NbO
[14] Q X Duan, Z K Jing, K Yang et al. Oscillation neuron based on threshold switching characteristics of niobium oxide films. 2019 IEEE International Workshop on Future Computing, 1(2019).
[15] J Woo, P N Wang, S M Yu. Integrated crossbar array with resistive synapses and oscillation neurons. IEEE Electron Device Lett, 40, 1313(2019).
[16] P N Wang, A I Khan, S M Yu. Cryogenic behavior of NbO2 based threshold switching devices as oscillation neurons. Appl Phys Lett, 116, 162108(2020).
[17] Q Luo, X Xu, H Lv et al. Cu BEOL compatible selector with high selectivity (> 107), extremely low off-current (pA) and high endurance (> 1010). 2015 IEEE International Electron Devices Meeting (IEDM), 10.4.1(2015).
[18] J Yoo, J Woo, J Song et al. Threshold switching behavior of Ag-Si based selector device and hydrogen doping effect on its characteristics. AIP Adv, 5, 127221(2015).
[19] G Du, C Wang, H X Li et al. Bidirectional threshold switching characteristics in Ag/ZrO2/Pt electrochemical metallization cells. AIP Adv, 6, 085316(2016).
[20] Z R Wang, M Y Rao, R Midya et al. Threshold switching: Threshold switching of Ag or Cu in dielectrics: Materials, mechanism, and applications. Adv Funct Mater, 28, 1870036(2018).
[21] J Yoo, J Park, J Song et al. Field-induced nucleation in threshold switching characteristics of electrochemical metallization devices. Appl Phys Lett, 111, 063109(2017).
[22] W Wang, M Wang, E Ambrosi et al. Surface diffusion-limited lifetime of silver and copper nanofilaments in resistive switching devices. Nat Commun, 10, 81(2019).
[23] Q L Hua, H Q Wu, B Gao et al. Threshold switching selectors: A threshold switching selector based on highly ordered Ag nanodots for X-point memory applications. Adv Sci, 6, 1970058(2019).
[24] Y J Li, J S Tang, B Gao et al. High-uniformity threshold switching HfO2 -based selectors with patterned Ag nanodots. Adv Sci, 7, 2002251(2020).
[25] Y Xi, B Gao, J S Tang et al. In-memory learning with analog resistive switching memory: A review and perspective. Proc IEEE, 109, 14(2021).
Get Citation
Copy Citation Text
Yujia Li, Jianshi Tang, Bin Gao, Xinyi Li, Yue Xi, Wanrong Zhang, He Qian, Huaqiang Wu. Oscillation neuron based on a low-variability threshold switching device for high-performance neuromorphic computing[J]. Journal of Semiconductors, 2021, 42(6): 064101
Category: Articles
Received: Jan. 6, 2021
Accepted: --
Published Online: Jun. 17, 2021
The Author Email: