283 related articles for article (PubMed ID: 26446303)
1. A Unified Framework for Reservoir Computing and Extreme Learning Machines based on a Single Time-delayed Neuron.
Ortín S; Soriano MC; Pesquera L; Brunner D; San-Martín D; Fischer I; Mirasso CR; Gutiérrez JM
Sci Rep; 2015 Oct; 5():14945. PubMed ID: 26446303
[TBL] [Abstract][Full Text] [Related]
2. High-Density Liquid-State Machine Circuitry for Time-Series Forecasting.
Rosselló JL; Alomar ML; Morro A; Oliver A; Canals V
Int J Neural Syst; 2016 Aug; 26(5):1550036. PubMed ID: 26906454
[TBL] [Abstract][Full Text] [Related]
3. Recent advances in physical reservoir computing: A review.
Tanaka G; Yamane T; Héroux JB; Nakane R; Kanazawa N; Takeda S; Numata H; Nakano D; Hirose A
Neural Netw; 2019 Jul; 115():100-123. PubMed ID: 30981085
[TBL] [Abstract][Full Text] [Related]
4. Stochastic nonlinear time series forecasting using time-delay reservoir computers: performance and universality.
Grigoryeva L; Henriques J; Larger L; Ortega JP
Neural Netw; 2014 Jul; 55():59-71. PubMed ID: 24732236
[TBL] [Abstract][Full Text] [Related]
5. Recurrent kernel machines: computing with infinite echo state networks.
Hermans M; Schrauwen B
Neural Comput; 2012 Jan; 24(1):104-33. PubMed ID: 21851278
[TBL] [Abstract][Full Text] [Related]
6. Distributed computing methodology for training neural networks in an image-guided diagnostic application.
Plagianakos VP; Magoulas GD; Vrahatis MN
Comput Methods Programs Biomed; 2006 Mar; 81(3):228-35. PubMed ID: 16476503
[TBL] [Abstract][Full Text] [Related]
7. Reservoir computing and extreme learning machines for non-linear time-series data analysis.
Butcher JB; Verstraeten D; Schrauwen B; Day CR; Haycock PW
Neural Netw; 2013 Feb; 38():76-89. PubMed ID: 23275138
[TBL] [Abstract][Full Text] [Related]
8. Real-time computing without stable states: a new framework for neural computation based on perturbations.
Maass W; Natschläger T; Markram H
Neural Comput; 2002 Nov; 14(11):2531-60. PubMed ID: 12433288
[TBL] [Abstract][Full Text] [Related]
9. FPGA-Based Stochastic Echo State Networks for Time-Series Forecasting.
Alomar ML; Canals V; Perez-Mora N; Martínez-Moll V; Rosselló JL
Comput Intell Neurosci; 2016; 2016():3917892. PubMed ID: 26880876
[TBL] [Abstract][Full Text] [Related]
10. The combination of circle topology and leaky integrator neurons remarkably improves the performance of echo state network on time series prediction.
Xue F; Li Q; Li X
PLoS One; 2017; 12(7):e0181816. PubMed ID: 28759581
[TBL] [Abstract][Full Text] [Related]
11. Delay-based reservoir computing: noise effects in a combined analog and digital implementation.
Soriano MC; Ortín S; Keuninckx L; Appeltant L; Danckaert J; Pesquera L; van der Sande G
IEEE Trans Neural Netw Learn Syst; 2015 Feb; 26(2):388-93. PubMed ID: 25608295
[TBL] [Abstract][Full Text] [Related]
12. Photonic nonlinear transient computing with multiple-delay wavelength dynamics.
Martinenghi R; Rybalko S; Jacquot M; Chembo YK; Larger L
Phys Rev Lett; 2012 Jun; 108(24):244101. PubMed ID: 23004274
[TBL] [Abstract][Full Text] [Related]
13. An experimental unification of reservoir computing methods.
Verstraeten D; Schrauwen B; D'Haene M; Stroobandt D
Neural Netw; 2007 Apr; 20(3):391-403. PubMed ID: 17517492
[TBL] [Abstract][Full Text] [Related]
14. Machine learning based on reservoir computing with time-delayed optoelectronic and photonic systems.
Chembo YK
Chaos; 2020 Jan; 30(1):013111. PubMed ID: 32013503
[TBL] [Abstract][Full Text] [Related]
15. Rotating neurons for all-analog implementation of cyclic reservoir computing.
Liang X; Zhong Y; Tang J; Liu Z; Yao P; Sun K; Zhang Q; Gao B; Heidari H; Qian H; Wu H
Nat Commun; 2022 Mar; 13(1):1549. PubMed ID: 35322037
[TBL] [Abstract][Full Text] [Related]
16. A forecast-based STDP rule suitable for neuromorphic implementation.
Davies S; Galluppi F; Rast AD; Furber SB
Neural Netw; 2012 Aug; 32():3-14. PubMed ID: 22386500
[TBL] [Abstract][Full Text] [Related]
17. VLSI circuits implementing computational models of neocortical circuits.
Wijekoon JH; Dudek P
J Neurosci Methods; 2012 Sep; 210(1):93-109. PubMed ID: 22342970
[TBL] [Abstract][Full Text] [Related]
18. Nonlinear regularization path for quadratic loss support vector machines.
Karasuyama M; Takeuchi I
IEEE Trans Neural Netw; 2011 Oct; 22(10):1613-25. PubMed ID: 21880570
[TBL] [Abstract][Full Text] [Related]
19. Optimization and applications of echo state networks with leaky-integrator neurons.
Jaeger H; Lukosevicius M; Popovici D; Siewert U
Neural Netw; 2007 Apr; 20(3):335-52. PubMed ID: 17517495
[TBL] [Abstract][Full Text] [Related]
20. Learning to decode human emotions with Echo State Networks.
Bozhkov L; Koprinkova-Hristova P; Georgieva P
Neural Netw; 2016 Jun; 78():112-9. PubMed ID: 26422421
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]