Online dynamical learning and sequence memory with neuromorphic nanowire networks
Abstract Nanowire Networks (NWNs) belong to an emerging class of neuromorphic systems
that exploit the unique physical properties of nanostructured materials. In addition to their …
that exploit the unique physical properties of nanostructured materials. In addition to their …
Training end-to-end analog neural networks with equilibrium propagation
We introduce a principled method to train end-to-end analog neural networks by stochastic
gradient descent. In these analog neural networks, the weights to be adjusted are …
gradient descent. In these analog neural networks, the weights to be adjusted are …
Engineering Method for Tailoring Electrical Characteristics in TiN/TiO x /HfO x /Au Bi-Layer Oxide Memristive Devices
S Park, S Klett, T Ivanov, A Knauer, J Doell… - Frontiers in …, 2021 - frontiersin.org
Memristive devices have led to an increased interest in neuromorphic systems. However,
different device requirements are needed for the multitude of computation schemes used …
different device requirements are needed for the multitude of computation schemes used …
Periodicity Pitch Perception Part III: Sensibility and Pachinko Volatility
F Feldhoff, H Toepfer, T Harczos… - Frontiers in neuroscience, 2022 - frontiersin.org
Neuromorphic computer models are used to explain sensory perceptions. Auditory models
generate cochleagrams, which resemble the spike distributions in the auditory nerve …
generate cochleagrams, which resemble the spike distributions in the auditory nerve …