most citedHardware calibrated learning to compensate heterogeneity in analog RRAM-based Spiking Neural Networks

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cs.ET2020

Low Power In-Memory Implementation of Ternary Neural Networks with Resistive RAM-Based Synapse

Axel Laborieux, Marc Bocquet, Tifenn Hirtzlin +6

The design of systems implementing low precision neural networks with emerging memories such as resistive random access memory (RRAM) is a major lead for reducing the energy consum…