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#author("2019-09-12T09:02:06+09:00","default:asl_member","asl_member") #author("2019-09-12T09:02:15+09:00","default:asl_member","asl_member") [[Vu Huy The]] please add well known reference realetd to FT in neuromorphic. Pleases sort them by newest first. #COLOR(red){Please complte this survey by August 20, 2019} %%COLOR(red){Please complte this survey by August 20, 2019}%% -''2019'': J. Liu et al., [[Exploring Self-Repair in a Coupled Spiking Astrocyte Neural Network>https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8423789]], in IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 3, pp. 865-875, March 2019. doi: 10.1109/TNNLS.2018.2854291 -''2019'': Mengyun Liu et. al., [[Fault tolerance in neuromorphic computing systems>https://dl.acm.org/citation.cfm?id=3288743]], ASPDAC '19 Proceedings of the 24th Asia and South Pacific Design Automation Conference Pages 216-223, Tokyo, Japan — January 21 - 24, 2019 -''2019'': Z. Ye, R. Liu et.al., [[Evaluation of Radiation Effects in RRAM-Based Neuromorphic Computing System for Inference>https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8576612&tag=1]], in IEEE Transactions on Nuclear Science, vol. 66, no. 1, pp. 97-103, Jan. 2019. doi: 10.1109/TNS.2018.2886793 -''2019'' J. J. Zhang, K. Basu and S. Garg, [[Fault-tolerant Systolic Array Based Accelerators for Deep Neural Network Execution>https://ieeexplore.ieee.org/document/8709714]], in IEEE Design & Test. doi: 10.1109/MDAT.2019.2915656 -''2019'': L. Xia et.al., [[Fault-Tolerant Training Enabled by On-Line Fault Detection for RRAM-Based Neural Computing Systems>https://ieeexplore.ieee.org/document/8410484]], in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. doi: 10.1109/TCAD.2018.2855145 -''2019'': C. Torres-Huitzil and B. Girau, [[Fault and Error Tolerance in Neural Networks: A Review>https://ieeexplore.ieee.org/document/8013784]], in IEEE Access, vol. 5, pp. 17322-17341, 2017. doi: 10.1109/ACCESS.2017.2742698 -''2018'': J. Liu et.al., [[SPANNER: A Self-Repairing Spiking Neural Network Hardware Architecture>https://ieeexplore.ieee.org/document/7872403]], in IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 4, pp. 1287-1300, April 2018. - ''2018'': A. P. Johnson et al. [[Homeostatic Fault Tolerance in Spiking Neural Networks: A Dynamic Hardware Perspective>>https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7995041]], in IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 65, no. 2, pp. 687-699, Feb. 2018. doi: 10.1109/TCSI.2017.2726763 -''2017'': L. Xia et al., [[Fault-tolerant training with on-line fault detection for RRAM-based neural computing systems>https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8060317]], 2017 54th ACM/EDAC/IEEE Design Automation Conference (DAC), Austin, TX, 2017, pp. 1-6. doi: 10.1145/3061639.3062248 -''2015'': M. Naeem et.al., [[On the role of astroglial syncytia in self-repairing spiking neural networks>https://ieeexplore.ieee.org/document/7001695]], in IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 10, pp. 2370-2380, Oct. 2015. doi: 10.1109/TNNLS.2014.2382334
