Results 41 to 50 of about 1,614,108 (280)

Modeling Orientation Selectivity Using a Neuromorphic Multi-Chip System [PDF]

, 2006
Chicca E, Lichtsteiner P, Delbruck T, Indiveri G, Douglas RJ. Modeling Orientation Selectivity Using a Neuromorphic Multi-Chip System. Presented at the Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS).The growing interest in ...
Douglas, R. J., Indiveri, G., Chicca, Elisabetta ; https://orcid.org/, Lichtsteiner, P., Delbruck, T.   +4 more
core   +1 more source

Neuromorphic computing with spintronics

npj Spintronics
Abstract Spintronics and magnetic materials exhibit many physical phenomena that are promising for implementing neuromorphic computing natively in hardware. Here, we review the current state-of-the-art, focusing on the areas of spintronic synapses, neurons, and neural networks.
Marrows, C.H., Barker, J., Moore, T.A., Moorsom, T.   +3 more
openaire   +2 more sources

Neuromorphic Engineering: From Neural Systems to Brain-Like Engineered Systems [PDF]

, 2013
Morabito FC, Andreou AG, Chicca E. Neuromorphic Engineering: From Neural Systems to Brain-Like Engineered Systems. Neural Networks.
Andreou, Andreas G., Morabito, Francesco Carlo, Chicca, Elisabetta ; https://orcid.org/   +2 more
core   +1 more source

Neuromorphic computing for attitude estimation onboard quadrotors

, 2022
Compelling evidence has been given for the high energy efficiency and update rates of neuromorphic processors, with performance beyond what standard Von Neumann architectures can achieve. Such promising features could be advantageous in critical embedded
Dupeyroux, J.J.G. (author), de Croon, G.C.H.E., de Croon, G.C.H.E. (author), Stroobants, S. (author), Dupeyroux, J.J.G., Stroobants, S.   +5 more
core   +2 more sources

Magnetic Elements for Neuromorphic Computing [PDF]

Molecules, 2020
Neuromorphic computing is assumed to be significantly more energy efficient than, and at the same time expected to outperform, conventional computers in several applications, such as data classification, since it overcomes the so-called von Neumann bottleneck.
Tomasz Blachowicz, Andrea Ehrmann
openaire   +3 more sources

Integrated Neuromorphic Photonics: Synapses, Neurons, and Neural Networks

Advanced Photonics Research, 2021
Ever‐growing demands of bandwidth, computing speed, and power consumption are now accelerating the transformation of computing research, as work‐at‐home becomes a new normal.
Xuhan Guo, Jinlong Xiang, Yujia Zhang, Yikai Su   +3 more
doaj   +1 more source

Neuromorphic Computing - An Overview

CoRR
With traditional computing technologies reaching their limit, a new field has emerged seeking to follow the example of the human brain into a new era: neuromorphic computing. This paper provides an introduction to neuromorphic computing, why this and other new computing systems are needed, and what technologies currently exist in the neuromorphic field.
Benedikt Jung, Maximilian Kalcher, Merlin Marinova, Piper Powell, Esma Sakalli   +4 more
openaire   +2 more sources

Scalable network emulation on analog neuromorphic hardware

Frontiers in Neuroscience
We present a novel software feature for the BrainScaleS-2 accelerated neuromorphic platform that facilitates the partitioned emulation of large-scale spiking neural networks.
Elias Arnold, Philipp Spilger, Jan V. Straub, Eric Müller, Dominik Dold, Gabriele Meoni, Johannes Schemmel   +6 more
doaj   +1 more source

2022 roadmap on neuromorphic computing and engineering [PDF]

Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer
Bartolozzi, Chiara, Menzel, Stephan, Valentian, Alexandre, Markovic, Danijela, Le Gallo, Manuel, Thorpe, Simon, Redaelli, Andrea, Scherr, Franz, Christensen, Martin Ejsing, Dittmann, Regina, Liu, Shihchii, Li, Xuan, Milano, Gianluca, Panuccio, Gabriella, Sebastian, Abu, Bhaskaran, Harish, Mizrahi, Alice, Donati, Elisa, Spiga, Sabina, Liang, Shi-Jun, Pernice, Wolfram H. P., Neftci, Emre, Ramaswamy, Srikanth, Keene, Scott T., Posch, Christoph, Cleland, Thomas A., Tanaka, Gouhei, Slesazeck, Stefan, Indiveri, Giacomo, Tolu, Silvia, Yang, J. Joshua, Grollier, Julie, Panda, Priyadarshini, Furber, Steve, Holm, Sune, Maass, Wolfgang, Mahmud, Mufti, Tapson, Jonathan, Hosseini, Morteza, Christensen, Dennis, V, Galeazzi, Roberto, Feldmann, Johannes, Mohsenin, Tinoosh, Mazumder, Arnab Neelim, Salleo, Alberto, Yao, Peng, Kim, Youngeun, Datta, Suman, Lanza, Mario, Quill, Tyler J., Mikolajick, Thomas, Miao, Feng, Ielmini, Daniele, Pryds, N., Valov, Ilia, Ricciardi, Carlo, Vianello, Elisa, Strachan, John Paul, Linares-Barranco, Bernabe   +58 more
core   +1 more source

Intermediate Resistive State in Wafer‐Scale Vertical MoS2 Memristors Through Lateral Silver Filament Growth for Artificial Synapse Applications

Advanced Functional Materials, EarlyView.
In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa, Milan Buttberg, Ke Ran, Rana Walied Ahmad, Dennis Braun, Lukas Völkel, Jimin Lee, Sofía Cruces, Bart Macco, Bárbara Canto, Holger Lerch, Thorsten Wahlbrink, Holger Kalisch, Michael Heuken, Andrei Vescan, Joachim Mayer, Zhenxing Wang, Ilia Valov, Stephan Menzel, Max C. Lemme   +19 more
wiley   +1 more source