75 citations · 77 across the 5 of their papers we have counts for
5 papers
RingSim- An Agent-based Approach for Modelling Mesoscopic Magnetic Nanowire Networks
Ian T Vidamour, Guru Venkat, Charles Swindells +9
We describe 'RingSim', a phenomenological agent-based model that allows numerical simulation of magnetic nanowire networks with areas of hundreds of micrometers squared for duratio…
Noise-Aware Training of Neuromorphic Dynamic Device Networks
Luca Manneschi, Ian T. Vidamour, Kilian D. Stenning +13
Physical computing has the potential to enable widespread embodied intelligence by leveraging the intrinsic dynamics of complex systems for efficient sensing, processing, and inter…
A perspective on physical reservoir computing with nanomagnetic devices
Dan A Allwood, Matthew O A Ellis, David Griffin +11
Neural networks have revolutionized the area of artificial intelligence and introduced transformative applications to almost every scientific field and industry. However, this succ…
Quantifying the Computational Capability of a Nanomagnetic Reservoir Computing Platform with Emergent Magnetization Dynamics
Ian T Vidamour, Matthew O A Ellis, David Griffin +12
Devices based on arrays of interconnected magnetic nano-rings with emergent magnetization dynamics have recently been proposed for use in reservoir computing applications, but for…
Reservoir Computing with Magnetic Thin Films
Matthew Dale, David Griffin, Richard F. L. Evans +6
Advances in artificial intelligence are driven by technologies inspired by the brain, but these technologies are orders of magnitude less powerful and energy efficient than biologi…