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Power-MSE trade-off of Factorized Low-rank Approximated Computation Scheme with Memristors
Memristor crossbars enable analog vector-matrix multiplication (VMM) which is promising for machine learning applications. Scaling matrix entries to lower memristor conductance levels reduces power consumption but increases the impact of memristor programming noise on VMM accuracy. To investigate ho
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