ArticleScientific reports2015
A Unified Framework for Reservoir Computing and Extreme Learning Machines based on a Single Time-delayed Neuron.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Experimental memory control in continuous-variable optical quantum reservoir computing.Nature photonics · 2026Article
- Nonlinear inference capacity of fiber-optical extreme learning machines.Nanophotonics (Berlin, Germany) · 2025Article
- Optical neuromorphic computing via temporal up-sampling and trainable encoding on a telecom device platform.Nanophotonics (Berlin, Germany) · 2025Article
- Principles and metrics of extreme learning machines using a highly nonlinear fiber.Nanophotonics (Berlin, Germany) · 2025Article
- Optical next generation reservoir computing.Light, science & applications · 2025Article
- Efficient optimisation of physical reservoir computers using only a delayed input.Communications engineering · 2025Article
- Complex dynamics in nonlinear small time-delayed optoelectronic oscillator and application in fast reservoir computing and pulse generation.Scientific reports · 2024Article
- Pattern recognition in reciprocal space with a magnon-scattering reservoir.Nature communications · 2023Article
- Distinguishing artificial spin ice states using magnetoresistance effect for neuromorphic computing.Nature communications · 2023Article
- Real-time respiratory motion prediction using photonic reservoir computing.Scientific reports · 2023Article
- Parallel and deep reservoir computing using semiconductor lasers with optical feedback.Nanophotonics (Berlin, Germany) · 2023Article
- Physical deep learning with biologically inspired training method: gradient-free approach for physical hardware.Nature communications · 2022Article
- Rotating neurons for all-analog implementation of cyclic reservoir computing.Nature communications · 2022Article
- Photonic reinforcement learning based on optoelectronic reservoir computing.Scientific reports · 2022Article
- Photonic neuromorphic technologies in optical communications.Nanophotonics (Berlin, Germany) · 2022Review
- Reservoir Computing with Delayed Input for Fast and Easy Optimisation.Entropy (Basel, Switzerland) · 2021Article
- Reservoir computing based on a silicon microring and time multiplexing for binary and analog operations.Scientific reports · 2021Article
- Optoelectronic intelligence.Applied physics letters · 2021Article
- Fast physical repetitive patterns generation for masking in time-delay reservoir computing.Scientific reports · 2021Article
- A Multiple-Input Multiple-Output Reservoir Computing System Subject to Optoelectronic Feedbacks and Mutual Coupling.Entropy (Basel, Switzerland) · 2020Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper we present a unified framework for extreme learning machines and reservoir computing (echo state networks), which can be physically implemented using a single nonlinear neuron subject to delayed feedback. The reservoir is built within the delay-line, employing a number of "virtual" neurons. These virtual neurons receive random projections from the input layer containing the information to be processed. One key advantage of this approach is that it can be implemented efficiently in hardware. We show that the reservoir computing implementation, in this case optoelectronic, is also capable to realize extreme learning machines, demonstrating the unified framework for both schemes in software as well as in hardware.
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