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Time-Dependent Variability in RRAM-based Analog Neuromorphic System for Pattern Recognition

Kang, J, Yu, Z, Wu, L, Fang, Y, Wang, Z, Cai, Y, Ji, Z, Zhang, JF, Wang, R, Yang, Y and Huang, R (2017) Time-Dependent Variability in RRAM-based Analog Neuromorphic System for Pattern Recognition. In: Technical Digest of the IEEE International Electron Devices Meeting (IEDM), . (2017 International Electron Devices Meeting (IEDM),, 2nd-6th December 2017, San Fransisco, USA).

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For the first time, this work investigated the time dependent variability (TDV) in RRAMs and its interaction with the RRAM-based analog neuromorphic circuits for pattern recognition. It is found that even the circuits are well trained, the TDV effect can introduce non-negligible recognition accuracy drop during the operating condition. The impact of TDV on the neuromorphic circuits increases when higher resistances are used for the circuit implementation, challenging for the future low power operation. In addition, the impact of TDV cannot be suppressed by either scaling up with more synapses or increasing the response time and thus threatens both real-time and general-purpose applications with high accuracy requirements. Further study on different circuit configurations, operating conditions and training algorithms, provides guidelines for the practical hardware implementation.

Item Type: Conference or Workshop Item (Paper)
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Divisions: Electronics & Electrical Engineering (merged with Engineering 10 Aug 20)
Publisher: IEEE
Date Deposited: 12 Dec 2017 11:53
Last Modified: 13 Apr 2022 15:16
URI: https://researchonline.ljmu.ac.uk/id/eprint/7706
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