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Investigation of weight updating modes on oxide-based resistive switching memory synapse towards neuromorphic computing applications

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References

  1. Park S, Kim H, Choo M, et al. RRAM-based synapse for neuromorphic system with pattern recognition function. In: Proceedings of International Electron Devices Meeting, 2012

  2. Chang C C, Chen P C, Chou T, et al. Mitigating asymmetric nonlinear weight update effects in hardware neural network based on analog resistive synapse. IEEE J Emerg Sel Top Circ Syst, 2017, 8: 116–124

    Article  Google Scholar 

  3. Woo J, Yu S M. Resistive-memory-based analog synapse: the pursuit for linear and symmetric weight update. IEEE Nanotechnol Mag, 2018, 12: 36–44

    Article  Google Scholar 

  4. Lv H B, Xu X X, Yuan P, et al. BEOL based RRAM with one extra-mask for low cost, highly reliable embedded application in 28 nm node and beyond. In: Proceedings of IEEE International Electron Devices Meeting (IEDM), 2017

  5. Woo J, Moon K, Song J, et al. Improved synaptic behavior under identical pulses using AlOx/HfO2 bilayer RRAM array for neuromorphic systems. IEEE Electron Dev Lett, 2016, 37: 994–997

    Article  Google Scholar 

  6. Woo J, Moon K, Song J, et al. Optimized programming scheme enabling linear potentiation in filamentary HfO2 RRAM synapse for neuromorphic systems. IEEE Trans Electron Dev, 2016, 63: 5064–5067

    Article  Google Scholar 

  7. Gonzalez M B, Martin-Martinez J, Maestro M, et al. Investigation of filamentary current fluctuations features in the high-resistance state of Ni/HfO2-based RRAM. IEEE Trans Electron Dev, 2016, 63: 3116–3122

    Article  Google Scholar 

  8. Ninomiya T, Wei Z, Muraoka S, et al. Conductive filament scaling of TaOx bipolar ReRAM for improving data retention under low operation current. IEEE Trans Electron Dev, 2013, 60: 1384–1389

    Article  Google Scholar 

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Acknowledgements

This work was supported by the National Science and Technology Major Project of China (Grant No. 2017ZX02301007-001), National Natural Science Foundation of China (Grant Nos. 61922083, 61804167, 61834009, 61904200, 62025406, 61821091), and Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDB44000000).

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Correspondence to Hangbing Lv.

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Investigation of Weight Updating Modes on Oxide-based Resistive Switching Memory Synapse towards Neuromorphic Computing Application

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Ding, Q., Gong, T., Yu, J. et al. Investigation of weight updating modes on oxide-based resistive switching memory synapse towards neuromorphic computing applications. Sci. China Inf. Sci. 64, 219402 (2021). https://doi.org/10.1007/s11432-020-3127-x

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  • DOI: https://doi.org/10.1007/s11432-020-3127-x

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