9 citations · 9 across the 5 of their papers we have counts for
6 papers
Matching of signal, noise and hardware timescales for filtering and forecasting of correlated noise signals
Joshua Donald, Alex Gabbitas, Arthur G. T. Coveney +2
Physical reservoir computing exploits the nonlinear dynamics of physical systems to process time-dependent data with greater energy efficiency than conventional machine learning ap…
Scalable platform enabling reservoir computing with nanoporous oxide memristors for image recognition and time series prediction
Joshua Donald, Ben A. Johnson, Amir Mehrnejat +5
Typical mammal brains have some form of random connectivity between neurons. Reservoir computing, a neural network approach, uses random weights within its processing layer along w…
Stochastic Dynamics of Diffusive Memristor Blocks for Neuromorphic Computing
Wendy Otieno, Alex Gabbitas, Debi Pattnaik +3
Biological systems use neural circuits to integrate input information and produce outputs. Synaptic convergence, where multiple neurons converge their inputs onto a single downstre…
Stochastic Instabilities of the Diffusive Memristor
Amir Akther, Debi Pattnaik, Yury Ushakov +3
Recently created diffusive memristors have garnered significant research interest owing to their distinctive capability to generate a diverse array of spike dynamics which are simi…
Memristive behavior of functionalized graphene quantum dot and polyaniline nanocomposites
Debi Prasad Pattnaik, Abu Bakar Siddique, Alex T. Bregazzi +4
Zero-dimensional graphene quantum dots (GQD) dispersed in conducting polymer matrix display a striking range of optical, mechanical, and thermoelectric properties which can be util…
Stress-induced Artificial neuron spiking in Diffusive memristors
Debi Pattnaik, Yash Sharma, Sergey Saveliev +4
Diffusive memristors owing to their ability to produce current spiking when a constant or slowly changing voltage is applied are competitive candidates for the development of artif…