The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A Unified Framework for Reservoir Computing and Extreme Learning Machines based on a Single Time-delayed Neuron
Open accessAbstract
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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Citations
Cites
Harnessing Nonlinearity: Predicting Chaotic Systems and Saving Energy in Wireless Communication
Jaeger, H., & Haas, H. (2004) · Science · doi:10.1126/science.1091277 · Cited by 3,811
Reservoir computing approaches to recurrent neural network training
Lukoševičius, M., & Jaeger, H. (2009) · Computer Science Review · doi:10.1016/j.cosrev.2009.03.005 · Cited by 2,956
Cited by
Recent advances in physical reservoir computing: A review
Tanaka, G., Yamane, T., Héroux, J. B., Nakane, R., Kanazawa, N., Takeda, S., Numata, H., Nakano, D., & Hirose, A. (2019) · Neural Networks · doi:10.1016/j.neunet.2019.03.005 · Cited by 2,146
Reinforcement learning in a large-scale photonic recurrent neural network
Bueno, J., Maktoobi, S., Froehly, L., Fischer, I., Jacquot, M., Larger, L., & Brunner, D. (2018) · Optica · doi:10.1364/optica.5.000756 · Cited by 403
Self-citationSilicon Photonic Modulator Neuron
Tait, A. N., Ferreira de Lima, T., Nahmias, M. A., Miller, H. B., Peng, H.-T., Shastri, B. J., & Prucnal, P. R. (2019) · Physical Review Applied · doi:10.1103/physrevapplied.11.064043 · Cited by 331
A Fast Machine Learning Model for ECG-Based Heartbeat Classification and Arrhythmia Detection
Alfaras, M., Soriano, M. C., & Ortín, S. (2019) · Frontiers in Physics · doi:10.3389/fphy.2019.00103 · Cited by 265
Self-citationDopant network processing units as tuneable extreme learning machines
van de Ven, B., Alegre-Ibarra, U., Lemieszczuk, P. J., Bobbert, P. A., Ruiz Euler, H.-C., & van der Wiel, W. G. (2023) · Frontiers in Nanotechnology · doi:10.3389/fnano.2023.1055527 · Cited by 2
Metadata
- Authors
- Ortín, S., Soriano, M. C., Pesquera, L., Brunner, D., San-Martín, D., Fischer, I., Mirasso, C. R., & Gutiérrez, J. M.
- Venue
- Scientific Reports
- Published
- 2015-10-08
- Volume
- 5
- Issue
- 1
- Pages
- 14945-14945
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W2256527444
- Cited by
- 191
- References
- 2
- FWCI
- 11.26
- Type
- journal article
- Language
- en
- Open access
- gold
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