Local inhomogeneities enable phase-dependent non-adiabatic parametric amplification of propagating spin waves in YIG nanostructures via momentum scattering, as shown by micromagnetic simulations and Brillouin light scattering experiments.
Performance enhancement of a spin-wave-based reservoir computing system utilizing different physical conditions
2 Pith papers cite this work. Polarity classification is still indexing.
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Spin wave-based physical reservoir computing achieves 85.8% speaker classification accuracy without cochleagram preprocessing.
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Phase-dependent parametric amplification of propagating spin waves in YIG nanostructures enabled by local inhomogeneities
Local inhomogeneities enable phase-dependent non-adiabatic parametric amplification of propagating spin waves in YIG nanostructures via momentum scattering, as shown by micromagnetic simulations and Brillouin light scattering experiments.
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Spoken Digit Recognition and Speaker Classification by Nonlinear Interfered Spin Wave-Based Physical Reservoir Computing
Spin wave-based physical reservoir computing achieves 85.8% speaker classification accuracy without cochleagram preprocessing.