Results 11 to 20 of about 10,442 (302)

A versatile neuromorphic system based on simple neuron model

AIP Advances, 2019
Brain-inspired neuromorphic computing has attracted much attention for its advanced computing concept. However, the massive hardware cost in fully-connected architectures makes it challenging to build a large-scale neuromorphic system.
C. M. Zhang, G. C. Qiao, S. G. Hu, J. J. Wang, Z. W. Liu, Y. A. Liu, Q. Yu, Y. Liu   +7 more
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NeuroPong: the event-based camera driven embedded neuromorphic system

Neuromorphic Computing and Engineering
Neuromorphic computing is a novel style of computing that features low-power spiking neural networks (SNNs) as the main compute components. It is an event-driven computational paradigm that naturally pairs with event-based cameras and their asynchronous ...
Charles P Rizzo, Bryson Gullett, Alex M Crumley, Maxwell E Marcum, Mason R Hyman, Carter Earheart-Brown, Julia Steed, Frank Standaert, Catherine D Schuman, James S Plank   +9 more
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Neuromorphic electronic systems [PDF]

Proceedings of the IEEE, 1990
It is shown that for many problems, particularly those in which the input data are ill-conditioned and the computation can be specified in a relative manner, biological solutions are many orders of magnitude more effective than those using digital methods.
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Artificial cognitive systems: From VLSI networks of spiking neurons to neuromorphic cognition [PDF]

, 2009
Neuromorphic engineering (NE) is an emerging research field that has been attempting to identify neural types of computational principles, by implementing biophysically realistic models of neural systems in Very Large Scale Integration (VLSI) technology.
Douglas, R J, Chicca, E, Douglas, R. J., Douglas, Rodney J., Indiveri, G, Indiveri, G., Indiveri, Giacomo, Chicca, Elisabetta, Chicca, Elisabetta ; https://orcid.org/   +8 more
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Integration of neuromorphic AI in event-driven distributed digitized systems: Concepts and research directions

Frontiers in Neuroscience, 2023
Increasing complexity and data-generation rates in cyber-physical systems and the industrial Internet of things are calling for a corresponding increase in AI capabilities at the resource-constrained edges of the Internet.
Mattias Nilsson, Olov Schelén, Anders Lindgren, Anders Lindgren, Ulf Bodin, Cristina Paniagua, Jerker Delsing, Fredrik Sandin   +7 more
doaj   +1 more source

Artificial Resilience in neuromorphic systems

International Symposium on Highly-Efficient Accelerators and Reconfigurable Technologies, 2022
Biological beings are intrinsically resilient. This means that they are able to continue to perform a task even if they are partially damaged or if some parts of them don’t work as expected. This is true also for the human brain. The research in these last years, however, has been concentrated on Artificial Intelligence (AI), to try to emulate the ...
Carpegna, Alessio, Di Carlo, Stefano, Savino, Alessandro   +2 more
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Emergent auditory feature tuning in a real-time neuromorphic VLSI system [PDF]

, 2012
Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic ...
Martin eCoath, Giacomo eIndiveri, Elisabetta eChicca, Sadique Sheik, Martin Coath, Wennekers, Thomas, Chicca, E, Susan L Denham, Thomas eWennekers, Elisabetta Chicca, Chicca, Elisabetta ; https://orcid.org/, Coath, Martin, Indiveri, G, Indiveri, Giacomo; id_orcid, Denham, Susan L., Coath, M, Chicca, Elisabetta, Sheik, S, Sadique eSheik, Denham, S L, Sheik, Sadique, Wennekers, T, Giacomo Indiveri, Susan L. Denham, Indiveri, Giacomo, Thomas Wennekers   +25 more
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Evolutionary Optimization for Neuromorphic Systems

Proceedings of the Neuro-inspired Computational Elements Workshop, 2020
Designing and training an appropriate spiking neural network for neuromorphic deployment remains an open challenge in neuromorphic computing. In 2016, we introduced an approach for utilizing evolutionary optimization to address this challenge called Evolutionary Optimization for Neuromorphic Systems (EONS).
Catherine D. Schuman, J. Parker Mitchell, Robert M. Patton, Thomas E. Potok, James S. Plank   +4 more
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Self-organized nanoscale networks: are neuromorphic properties conserved in realistic device geometries? [PDF]

, 2023
Self-organised nanoscale networks are currently under investigation because of their potential to be used as novel neuromorphic computing systems. In these systems, electrical input and output signals will necessarily couple to the recurrent electrical ...
Acharya, S, Heywood, Z, Arnold, M, Brown, S, Bones, P, Bose, S, Mallinson, J, Galli, E   +7 more
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Variational learning of quantum ground states on spiking neuromorphic hardware [PDF]

, 2022
Recent research has demonstrated the usefulness of neural networks as variational ansatz functions for quantum many-body states. However, high-dimensional sampling spaces and transient autocorrelations confront these approaches with a challenging ...
Gärttner, Martin, Baumbach, Andreas, Petrovici, Mihai A., Klassert, Robert, Petrovici, Mihai A   +4 more
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