Reservoir Computing Using Diffusive Memristors

High Performance Silver Diffusive Memristors for Future Computing

Reservoir Computing using Cellular Automata

We introduce a novel framework of reservoir computing. Cellular automaton is used as the reservoir of dynamical systems. Input is randomly projected onto the initial conditions of automaton cells and nonlinear computation is performed on the input via application of a rule in the automaton for a period of time. The evolution of the automaton creates a space-time volume of the automaton state sp...

Visualising Temporal Data Using Reservoir Computing

We create an artificial neural network which is a version of echo state machines, ESNs. ESNs are recurrent neural networks but unlike most recurrent networks, they come with an efficient training method. We adapt this method using ideas from the neuroscale algorithm so that the network is optimal for projecting multivariate time series data onto a low dimensional manifold so that the structure ...

Epileptic seizure detection using Reservoir Computing

In this paper it is shown that Reservoir Computing can be successfully applied to perform real-time detection of epileptic seizures in Electroencephalograms (EEGs). Absence and tonic-clonic seizures are detected on intracranial EEG coming from rats. This resulted in an area under the Receiver Operating Characteristics (ROC) curve of more than 0.99 on the data that was used. For absences an aver...

Reservoir Computing using Stochastic p-Bits

We present a general hardware framework for building networks that directly implement Reservoir Computing, a popular software method for implementing and training Recurrent Neural Networks and are particularly suited for temporal inferencing and pattern recognition. We provide a specific example of a candidate hardware unit based on a combination of soft-magnets, spin-orbit materials and CMOS t...