Towards an Expressivity-Normalized Energy-Demand Comparison of ANNs and SNNs
An analytical framework is developed to compare fully-connected ReLU ANNs and integrate-and-fire SNNs for time-series data with respect to their theoretical energy efficiency at matched expressive capacity, and derives an expressivity-normalized efficiency ratio and explicit thresholds in network width, spike sparsity,...
Miriam Kranzlmüller, P. Esser, Gitta Kutyniok
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