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

Spiking Neural Networks (SNNs) can unleash the full power of analog Resistive Random Access Memories (RRAMs) based circuits for low power signal processing. Their inherent computational sparsity naturally results in energy efficiency benefits. The main challenge implementing robust SNNs is the intri...

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Bibliographische Detailangaben

Hauptverfasser:	Moro, Filippo, Esmanhotto, E, Hirtzlin, T, Castellani, N, Trabelsi, A, Dalgaty, T, Molas, G, Andrieu, F, Brivio, S, Spiga, S, Indiveri, G, Payvand, M, Vianello, E
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Neural and Evolutionary Computing
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