6 citations · 8 across the 3 of their papers we have counts for
3 papers
A Compact Model of Interface-Type Memristors Linking Physical and Device Properties
T. F. Tiotto, A. S. Goossens, A. E. Dima +4
Memristors are an electronic device whose resistance depends on the voltage history that has been applied to its two terminals. Despite its clear advantage as a computational eleme…
A Robust Learning Rule for Soft-Bounded Memristive Synapses Competitive with Supervised Learning in Standard Spiking Neural Networks
Thomas F. Tiotto, Jelmer P. Borst, Niels A. Taatgen
Memristive devices are a class of circuit elements that shows great promise as future building block for brain-inspired computing. One influential view in theoretical neuroscience…
Learning to Approximate Functions Using Nb-doped SrTiO Memristors
Thomas F. Tiotto, Anouk S. Goossens, Jelmer P. Borst +2
Memristors have attracted interest as neuromorphic computation elements because they show promise in enabling efficient hardware implementations of artificial neurons and synapses.…