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Nanopositioning for probe storage., , , , , and . ACC, page 4181-4186. IEEE, (2005)Biologically Inspired Dynamics Enhance Deep Learning., , and . ERCIM News, (2021)Feature Learning Using Synaptic Competition in a Dynamically-Sized Neuromorphic Architecture., , , and . ICRC, page 1-7. IEEE, (2017)Neuromorphic system with phase-change synapses for pattern learning and feature extraction., , , and . IJCNN, page 3724-3732. IEEE, (2017)Learning-to-learn enables rapid learning with phase-change memory-based in-memory computing., , , , , , , , , and . CoRR, (2024)Optimal scan trajectories for high-speed scanning probe microscopy., , , and . ACC, page 3791-3796. IEEE, (2012)Nanoscale track-following for tape storage., , , , , and . ACC, page 2837-2843. IEEE, (2015)Two-sensor-based H∞ control for nanopositioning in probe storage., , , and . CDC/ECC, page 1174-1179. IEEE, (2005)Dynamic event-based optical identification and communication., , , , and . Frontiers Neurorobotics, (2024)Biologically-inspired training of spiking recurrent neural networks with neuromorphic hardware., , , , , , , and . AICAS, page 218-221. IEEE, (2022)