Project description
Implementing brain-inspired computing in the reciprocal space of a single magnetic element
Artificial neural networks are computing systems inspired by biological neural networks. They emulate the brain by using nonlinear elements that act as neurons interconnected through artificial synapses. Current architectures are facing challenges: the number of synapses implemented is very limited compared with the tens of thousands in the human brain. Furthermore, changing the weight of each connection requires additional memory elements. The EU-funded k-NET project will circumvent these issues. It proposes new architecture based on the idea that dynamical hyperconnectivity can be implemented not in real space but in reciprocal or k-space. To demonstrate this novel approach, researchers will select ferromagnetic nanostructures in which the populations of spin waves – the elementary excitations – play the role of neurons.
Fields of science
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
75794 Paris
France
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Participants (7)
Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
91190 Gif-sur-yvette
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28006 Madrid
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75015 Paris 15
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48149 Muenster
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80125 Napoli
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1088 Budapest
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92400 Courbevoie
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