Hardware calibrated learning to compensate heterogeneity in analog RRAM-based Spiking Neural Networks - researchr publication authors

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Filippo Moro, Eduardo Esmanhotto, Tifenn Hirtzlin, Niccolo Castellani, A. Trabelsi, Thomas Dalgaty, Gabriel Molas, François Andrieu, Stefano Brivio, Sabina Spiga, Giacomo Indiveri, Melika Payvand, Elisa Vianello. Hardware calibrated learning to compensate heterogeneity in analog RRAM-based Spiking Neural Networks. In IEEE International Symposium on Circuits and Systems, ISCAS 2022, Austin, TX, USA, May 27 - June 1, 2022. pages 380-383, IEEE, 2022. [doi]

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