The International Journal of Fuzzy Logic and Intelligent Systems

eISSN 2093-744X
pISSN 1598-2645

ANN-SNN conversion algorithms

AlgorithmNeuron modelArchitectureInput encodingOutput decodingFeatures
soft-LIF (2015, [44])soft-LIF (ANN)LIF (SNN)Deep networkSpike train (rate code)Spike train (firing rate)Use soft-LIF in ANN for LIF
Cao et al. (2015, [45])ReLU (ANN)IF (SNN)Shallow networkSpike train (rate code)Spike train (firing rate)Constrained arch.; avg. pooling, no bias
Diehl et al. (2015, [46])ReLU (ANN)IF (SNN)Shallow networkSpike train (rate code)Spike train (firing rate)Constrained arch.; weight normalization
Rueckauer et al. (2017, [30])ReLU (ANN)IF (SNN)Deep networkDirect inputSpike train (firing rate)Constrained arch.; batch norm.; softmax
Whetstone (2018, [47])bReLU (ANN)IF (SNN)Deep networkSpike train (rate code)Spike train (firing rate)Adaptive sharpening of activation function
Sengupta et al. (2019, [48])ReLU (ANN)IF (SNN)Deep networkSpike train (rate code)Spike train (firing rate)Normalization in SNN; Spike-Norm
RMP-SNN (2020, [49])ReLU (ANN)IF (SNN)Deep networkSpike train (rate code)Spike train (firing rate)IF with soft-reset; control threshold range; threshold balancing
Deng et al. (2021, [50])thr. ReLU (ANN)IF (SNN)Deep networkSpike train (rate code)Spike train (firing rate)Conversion loss-aware bias adaptation; threshold ReLU; shifted bias
Ding et al. (2021, [51])RNL (ANN)IF (SNN)Deep networkSpike train (rate code)Spike train (rate code)Optimal scaling factors for threshold balancing
Patel et al. (2021, [52])mod. ReLU (ANN)IF (SNN)Scaled-downU-NetSpike train (rate code)Spike train (rate code)image segmentation Loihi deployment
International Journal of Fuzzy Logic and Intelligent Systems 2021;21:317~337 https://doi.org/10.5391/IJFIS.2021.21.4.317
© IJFIS
Copyright © The Korean Institute of Intelligent Systems. / Powered by INFOrang Co., Ltd