The Characteristics of Binary Spike-Time-Dependent Plasticity in HfO2-Based RRAM and Applications for Pattern Recognition

Abstract A binary spike-time-dependent plasticity (STDP) protocol based on one resistive-switching random access memory (RRAM) device was proposed and experimentally demonstrated in the fabricated RRAM array. Based on the STDP protocol, a novel unsupervised online pattern recognition system includin...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:Nanoscale Research Letters
المؤلفون الرئيسيون: Zheng Zhou, Chen Liu, Wensheng Shen, Zhen Dong, Zhe Chen, Peng Huang, Lifeng Liu, Xiaoyan Liu, Jinfeng Kang
التنسيق: مقال
اللغة:الإنجليزية
منشور في: SpringerOpen 2017-04-01
الموضوعات:
RRAM
ALD
STDP
Unsupervised online learning
Pattern recognition
الوصول للمادة أونلاين:http://link.springer.com/article/10.1186/s11671-017-2023-y
الوصف
الملخص:Abstract A binary spike-time-dependent plasticity (STDP) protocol based on one resistive-switching random access memory (RRAM) device was proposed and experimentally demonstrated in the fabricated RRAM array. Based on the STDP protocol, a novel unsupervised online pattern recognition system including RRAM synapses and CMOS neurons is developed. Our simulations show that the system can efficiently compete the handwritten digits recognition task, which indicates the feasibility of using the RRAM-based binary STDP protocol in neuromorphic computing systems to obtain good performance.
تدمد:1931-7573
1556-276X

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