The aim of the work was to interpret and classify in a brain-inspired manner dynamic spatio-temporal brain signals and demonstrate improved classification ...
Reservoir computing is a machine learning method that is closely linked to dynamical systems theory. This connection is highlighted in a brief introduction ...
Reservoir computing consists of a recurrent neural network with a reservoir layer and a readout layer. By utilizing nonlinear spatial-temporal patterns against ...
Abstract. Reservoir computing (RC) studies the properties of large recurrent networks of artificial neurons, with either fixed or random con- nectivity.
The aim of this Special Issue is to focus on new challenges for fully exploiting the potential of RC in machine learning applications and realizing extremely ...
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What is the reservoir computing approach?
Jul 16, 2024 · In reservoir computing, the input time-series data are transformed into spatio-temporal patterns in the reservoir layer. The responses of ...
Topics of the special session: Novel Reservoir Computing models Deep Reservoir Computing Reservoir Computing for Big Data Physical, Neuromorphic and Photonic ...
Jun 1, 2022 · Reservoir computing (RC) is an ML framework leveraging a dynamic reservoir for a nonlinear transformation of sequential inputs and a readout for mapping the ...
Mar 6, 2024 · This Perspective intends to elucidate the parallel progress of mathematical theory, algorithm design and experimental realizations of reservoir computing.
Reservoir computing (RC) studies the properties of large recurrent networks of artificial neurons, with either fixed or random connectivity. Over the last years ...