1 code implementation • 28 Aug 2021 • Felix Köster, Serhiy Yanchuk, Kathy Lüdge
We show that many delay-based reservoir computers considered in the literature can be characterized by a universal master memory function (MMF).
no code implementations • 14 Jan 2021 • Simon Vock, Rico Berner, Serhiy Yanchuk, Eckehard Schöll
Using numerical and analytical approaches, we investigate the robustness of multicluster states on networks of adaptively coupled Kuramoto-Sakaguchi oscillators against the random dilution of the underlying network topology.
Adaptation and Self-Organizing Systems Pattern Formation and Solitons
no code implementations • 8 Jan 2021 • Florian Stelzer, Serhiy Yanchuk
The method recently introduced in arXiv:2011. 10115 realizes a deep neural network with just a single nonlinear element and delayed feedback.
1 code implementation • 19 Nov 2020 • Florian Stelzer, André Röhm, Raul Vicente, Ingo Fischer, Serhiy Yanchuk
We present a method for folding a deep neural network of arbitrary size into a single neuron with multiple time-delayed feedback loops.
no code implementations • 16 Sep 2020 • Felix Köster, Serhiy Yanchuk, Kathy Lüdge
In this paper we give a profound insight into the computation capability of delay-based reservoir computing via an eigenvalue analysis.
no code implementations • 11 Jun 2020 • Mirko Goldmann, Felix Köster, Kathy Lüdge, Serhiy Yanchuk
We present how the dynamical properties of a deep Ikeda-based reservoir are related to its memory capacity (MC) and how that can be used for optimization.
no code implementations • 7 May 2019 • Florian Stelzer, André Röhm, Kathy Lüdge, Serhiy Yanchuk
Here we show that the case of equal or resonant time-delay and clock cycle could be actively detrimental and leads to an increase of the approximation error of the reservoir.