TY - GEN
T1 - Long-term memory performance with learning behavior of artificial synaptic memristor based on stacked solution-processed switching layers
AU - Shen, Zongjie
AU - Zhao, Chun
AU - Man, Ka Lok
AU - Liu, Yina
AU - Zhao, Cezhou
N1 - Funding Information:
ACKNOWLEDGMENT This research was funded in part by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China Program (19KJB510059), the Suzhou Science and Technology Development Planning Project: Key Industrial Technology Innovation (SYG201924), and the Key Program Special Fund in XJTLU (KSF-P-02, KSF-T-03, KSF-A-04, KSF-A-05, KSF-A-07).
Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - In this work, oxide resistive random access memory (OxRRAM) devices with stacked solution-processed (SP) metal oxide (MO) layers were fabricated to investigate artificial synaptic behavior such as long-term potentiation (LTP) and long-term depression (LTD). The stacked RRAM devices exhibited stable and repeated bipolar IV curves with operation voltage lower than the ~0.5 V and a switching ratio larger than 2×104. Also, with the stimuli from external consecutive pulses, the stacked devices demonstrated learning-forgetting-relearning behavior similar to neuron-induced behavior in the human brain. Finally, based on stable long-term memory performance, the pattern recognition system with an artificial neuron network (ANN) algorithm was simulated with the recognition accuracy higher than 95%.
AB - In this work, oxide resistive random access memory (OxRRAM) devices with stacked solution-processed (SP) metal oxide (MO) layers were fabricated to investigate artificial synaptic behavior such as long-term potentiation (LTP) and long-term depression (LTD). The stacked RRAM devices exhibited stable and repeated bipolar IV curves with operation voltage lower than the ~0.5 V and a switching ratio larger than 2×104. Also, with the stimuli from external consecutive pulses, the stacked devices demonstrated learning-forgetting-relearning behavior similar to neuron-induced behavior in the human brain. Finally, based on stable long-term memory performance, the pattern recognition system with an artificial neuron network (ANN) algorithm was simulated with the recognition accuracy higher than 95%.
KW - Human brain
KW - RRAM
KW - Solution-processed
KW - Synaptic behavior
UR - http://www.scopus.com/inward/record.url?scp=85109015427&partnerID=8YFLogxK
U2 - 10.1109/ISCAS51556.2021.9401493
DO - 10.1109/ISCAS51556.2021.9401493
M3 - Conference Proceeding
AN - SCOPUS:85109015427
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
BT - 2021 IEEE International Symposium on Circuits and Systems, ISCAS 2021 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 53rd IEEE International Symposium on Circuits and Systems, ISCAS 2021
Y2 - 22 May 2021 through 28 May 2021
ER -