Improved Synaptic Characteristics in Bilayer Memristor by Post-Oxide Deposition Annealing for Pattern Recognition

Dayanand Kumar; Yi Rong Huang; Pratibha Pal; Aftab Saleem; Amit Singh; Hoonkyung Lee; Yeong Her Wang; Tseung Yuen Tseng

doi:10.1109/VLSI-TSA54299.2022.9771007

Improved Synaptic Characteristics in Bilayer Memristor by Post-Oxide Deposition Annealing for Pattern Recognition

Dayanand Kumar^*, Yi Rong Huang, Pratibha Pal, Aftab Saleem, Amit Singh, Hoonkyung Lee, Yeong Her Wang, Tseung Yuen Tseng

^*Corresponding author for this work

Institute of Electronics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We present highly stable bilayer HfO2/TiO2 memristive synapse for neuromorphic computing applications. The memristive synapse shows repetitive 220 Long-term potentiation and depression cycles without any breakdown with total number of 220k pulses. The nonlinear values of potentiation and depression are 2.52 and -2.63, respectively with 1000 conductance pulses (500 pulses of potentiation and 500 pulses of depression). The experimental data of potentiation and depression was used to train HNN for pattern recognition of 28×28 pixels comprising 784 synapses. In 16 iterations, the HNN can be successfully trained to identify the input image with a training accuracy of about 97%. Moreover, the device has good retention (104 s) at 120 °C. These excellent synaptic characteristics of annealed device allows it for artificial intelligence systems in near future.

Original language	English
Title of host publication	2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665409230
DOIs	https://doi.org/10.1109/VLSI-TSA54299.2022.9771007
State	Published - 2022
Event	2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022 - Hsinchu, Taiwan Duration: 18 Apr 2022 → 21 Apr 2022

Publication series

Name	2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022

Conference

Conference	2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022
Country/Territory	Taiwan
City	Hsinchu
Period	18/04/22 → 21/04/22

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10.1109/VLSI-TSA54299.2022.9771007

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Kumar, D., Huang, Y. R., Pal, P., Saleem, A., Singh, A., Lee, H., Wang, Y. H., & Tseng, T. Y. (2022). Improved Synaptic Characteristics in Bilayer Memristor by Post-Oxide Deposition Annealing for Pattern Recognition. In 2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022 (2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VLSI-TSA54299.2022.9771007

Kumar, Dayanand ; Huang, Yi Rong ; Pal, Pratibha et al. / Improved Synaptic Characteristics in Bilayer Memristor by Post-Oxide Deposition Annealing for Pattern Recognition. 2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022).

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title = "Improved Synaptic Characteristics in Bilayer Memristor by Post-Oxide Deposition Annealing for Pattern Recognition",

abstract = "We present highly stable bilayer HfO2/TiO2 memristive synapse for neuromorphic computing applications. The memristive synapse shows repetitive 220 Long-term potentiation and depression cycles without any breakdown with total number of 220k pulses. The nonlinear values of potentiation and depression are 2.52 and -2.63, respectively with 1000 conductance pulses (500 pulses of potentiation and 500 pulses of depression). The experimental data of potentiation and depression was used to train HNN for pattern recognition of 28×28 pixels comprising 784 synapses. In 16 iterations, the HNN can be successfully trained to identify the input image with a training accuracy of about 97%. Moreover, the device has good retention (104 s) at 120 °C. These excellent synaptic characteristics of annealed device allows it for artificial intelligence systems in near future.",

author = "Dayanand Kumar and Huang, {Yi Rong} and Pratibha Pal and Aftab Saleem and Amit Singh and Hoonkyung Lee and Wang, {Yeong Her} and Tseng, {Tseung Yuen}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; null ; Conference date: 18-04-2022 Through 21-04-2022",

year = "2022",

doi = "10.1109/VLSI-TSA54299.2022.9771007",

language = "English",

series = "2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022",

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Kumar, D, Huang, YR, Pal, P, Saleem, A, Singh, A, Lee, H, Wang, YH & Tseng, TY 2022, Improved Synaptic Characteristics in Bilayer Memristor by Post-Oxide Deposition Annealing for Pattern Recognition. in 2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022. 2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022, Institute of Electrical and Electronics Engineers Inc., 2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022, Hsinchu, Taiwan, 18/04/22. https://doi.org/10.1109/VLSI-TSA54299.2022.9771007

Improved Synaptic Characteristics in Bilayer Memristor by Post-Oxide Deposition Annealing for Pattern Recognition. / Kumar, Dayanand; Huang, Yi Rong; Pal, Pratibha et al.

2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Improved Synaptic Characteristics in Bilayer Memristor by Post-Oxide Deposition Annealing for Pattern Recognition

AU - Kumar, Dayanand

AU - Huang, Yi Rong

AU - Pal, Pratibha

AU - Saleem, Aftab

AU - Singh, Amit

AU - Lee, Hoonkyung

AU - Wang, Yeong Her

AU - Tseng, Tseung Yuen

PY - 2022

Y1 - 2022

N2 - We present highly stable bilayer HfO2/TiO2 memristive synapse for neuromorphic computing applications. The memristive synapse shows repetitive 220 Long-term potentiation and depression cycles without any breakdown with total number of 220k pulses. The nonlinear values of potentiation and depression are 2.52 and -2.63, respectively with 1000 conductance pulses (500 pulses of potentiation and 500 pulses of depression). The experimental data of potentiation and depression was used to train HNN for pattern recognition of 28×28 pixels comprising 784 synapses. In 16 iterations, the HNN can be successfully trained to identify the input image with a training accuracy of about 97%. Moreover, the device has good retention (104 s) at 120 °C. These excellent synaptic characteristics of annealed device allows it for artificial intelligence systems in near future.

AB - We present highly stable bilayer HfO2/TiO2 memristive synapse for neuromorphic computing applications. The memristive synapse shows repetitive 220 Long-term potentiation and depression cycles without any breakdown with total number of 220k pulses. The nonlinear values of potentiation and depression are 2.52 and -2.63, respectively with 1000 conductance pulses (500 pulses of potentiation and 500 pulses of depression). The experimental data of potentiation and depression was used to train HNN for pattern recognition of 28×28 pixels comprising 784 synapses. In 16 iterations, the HNN can be successfully trained to identify the input image with a training accuracy of about 97%. Moreover, the device has good retention (104 s) at 120 °C. These excellent synaptic characteristics of annealed device allows it for artificial intelligence systems in near future.

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M3 - Conference contribution

AN - SCOPUS:85130461520

T3 - 2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022

BT - 2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022

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Kumar D, Huang YR, Pal P, Saleem A, Singh A, Lee H et al. Improved Synaptic Characteristics in Bilayer Memristor by Post-Oxide Deposition Annealing for Pattern Recognition. In 2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022. Institute of Electrical and Electronics Engineers Inc. 2022. (2022 International Symposium on VLSI Technology, Systems and Applications, VLSI-TSA 2022). doi: 10.1109/VLSI-TSA54299.2022.9771007

Improved Synaptic Characteristics in Bilayer Memristor by Post-Oxide Deposition Annealing for Pattern Recognition

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