A substrate-independent framework to characterize reservoir computers
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Title
A substrate-independent framework to characterize reservoir computers
Authors
Keywords
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Journal
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
Volume 475, Issue 2226, Pages 20180723
Publisher
The Royal Society
Online
2019-06-19
DOI
10.1098/rspa.2018.0723
References
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- (2012) L. Larger et al. OPTICS EXPRESS
- Optoelectronic Reservoir Computing
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- Emergent Criticality in Complex Turing B-Type Atomic Switch Networks
- (2011) Adam Z. Stieg et al. ADVANCED MATERIALS
- Parallel Reservoir Computing Using Optical Amplifiers
- (2011) K. Vandoorne et al. IEEE TRANSACTIONS ON NEURAL NETWORKS
- Information processing using a single dynamical node as complex system
- (2011) L. Appeltant et al. Nature Communications
- Abandoning Objectives: Evolution Through the Search for Novelty Alone
- (2010) Joel Lehman et al. EVOLUTIONARY COMPUTATION
- Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons
- (2009) Lars Büsing et al. NEURAL COMPUTATION
- Memory traces in dynamical systems
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