Minimum Complexity Echo State Network
By Ali Rodan, Peter Tino. IEEE Transactions on Neural Networks, 2011
686 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/2a1b35eeeaa20e08777768fcf8b747ba20f5a888
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Ingo Fischer
- Miguel C. Soriano
- Claudio R. Mirasso
- Kohei Nakajima
- Serge Massar
- Daniel Brunner
- Joni Dambre
- Benjamin Schrauwen
In Electrical and Electronic Engineering
- Ingo Fischer
- Miguel C. Soriano
- Claudio R. Mirasso
- Kohei Nakajima
- Serge Massar
- Daniel Brunner
- Joni Dambre
- Benjamin Schrauwen
Citations in the corpus
- ECG-based heartbeat classification for arrhythmia detection: A survey (2016, background): “Reservoir computing with logistic regression (RC) According to Rodan and Tiňo [123], reservoir computing models are dynamical models aiming to process a time series signal in two parts: represent the signal through a nonadaptable dynamic reservoir and a dynamic readout from the reservoir.”
- All-optical Reservoir Computing (2012, background): “It has been shown [19,20] that even very simple interconnection matrices can lead to excellent results.”
- Optoelectronic Reservoir Computing (2011, methodology): “Before introducing our implementation, we recall a few key features of reservoir computing; for a more detailed treatment of the underlying theory, we refer the reader to Supplementary Material.”
- Parallel photonic information processing at gigabyte per second data rates using transient states (2013, background): “Theoretical 8,9 and experimental 7,10–12 investigations show that our scheme can indeed be interpreted as RC.”
- Emerging opportunities and challenges for the future of reservoir computing (2024, neutral): “…to as signal classi fi cation, nonlinear time series prediction, dynamical control and PDE computing, respectively. a RC forspoken-digit recognition 16,28,29,34,35,65,68,82 – 84 , when the targets are a vectorof digit numberscorresponding to 0 – 9. b RCfor time series prediction with…”
- Physical reservoir computing—an introductory perspective (2020, background): “Focusing on ESN, the behaviors of memory capacity and their related measures are studied in detail with a linear activation function [46–51] and, recently, with a nonlinear activation function [52–54].”
- A Practical Guide to Applying Echo State Networks (2012, neutral): “, [33], and data-specific, e.”