[1]

Ivakhnenko AG. Polynomial theory of complex systems. IEEE T Syst Man Cyb 1971;1:364–78. CrossrefGoogle Scholar

[2]

Cireşan D, Meier U, Maria Gambardella L, Schmidhuber J. Deep, big, simple neural nets for handwritten digit recognition. Neural Comput 2010;22:3207–20. CrossrefGoogle Scholar

[3]

Krizhevsky A, Sutskever I, Hinton G. Imagenet classification with deep convolutional neural networks. Adv Neural Inf Process Syst 2012;25:1106–14. Google Scholar

[4]

Silver D, Huang A, Maddison CJ, et al. Mastering the game of go with deep neural networks and tree search. Nature 2016;529:484–9. CrossrefGoogle Scholar

[5]

Merolla PA, Arthur J, Alvarez-Icaza R, et al. A million spiking-neuron integrated circuit with a scalable communication network and interface. Science 2014;345:668–72. CrossrefGoogle Scholar

[6]

Furber S, Temple S. Neural systems engineering. J R Soc Interf 2006;4:193–206. CrossrefGoogle Scholar

[7]

Rast A, Galluppi F, Davies S, et al. Concurrent heterogeneous neural model simulation on real-time neuromimetic hardware. Neural Networks 2011;24:961–78. CrossrefGoogle Scholar

[8]

Hopfield J, Tank D. “Neural” computation of decisions in optimization problems. Biol Cybern 1985;52:141–52. Google Scholar

[9]

Denz C. Optical neural networks. In: Tschudi T., ed. Wiesbaden, Springer Vieweg, 1998. Google Scholar

[10]

Psaltis D, Brady D, Gu X-G, Lin S. Holography in artificial neural networks. Nature 1990;343:325. CrossrefGoogle Scholar

[11]

Jutamulia S, Yu F. Overview of hybrid optical neural networks. Opt Laser Technol 1996;28:59–72. CrossrefGoogle Scholar

[12]

Fernando C, Sojakka S. Pattern recognition in a bucket. In: Banzhaf W., Ziegler J., Christaller T., Dittrich P., Kim J.T., eds. Advances in Artificial Life. ECAL 2003. Lecture Notes in Computer Science, vol 2801. Berlin, Heidelberg, Springer, 2003. Google Scholar

[13]

Jaeger H, Haas H. Harnessing nonlinearity: predicting chaotic systems and saving energy in wireless communication. Science 2004;304:78–80. CrossrefGoogle Scholar

[14]

Maass W, Natschläger T, Markram H. Real-time computing without stable states: a new framework for neural computation based on perturbations. Neural Comput 2002;14:2531–6. CrossrefGoogle Scholar

[15]

Steil J. Backpropagation-decorrelation: online recurrent learning with O(N) complexity. IJCNN 2004;1:843–8. Google Scholar

[16]

Lukoševičius M, Jaeger H. Reservoir computing approaches to recurrent neural network training. Comput Sci Rev 2009;3:127–49. CrossrefGoogle Scholar

[17]

Verstraeten D, Schrauwen B, D’Haene M, Stroobandt D. An experimental unification of reservoir computing methods. Neural Networks 2007;20:391–403. CrossrefGoogle Scholar

[18]

Jaeger H. Short term memory in echo state networks. German National Research Center for Information Technology, Technical Report GMD Report 152, 2001. Google Scholar

[19]

Rodan A, Tino P. Minimum complexity echo state network. IEEE Trans Neural Netw 2011;22:131–44. CrossrefGoogle Scholar

[20]

Appeltant L, Soriano MC, Van der Sande G, et al. Information processing using a single dynamical node as complex system. Nat Commun 2011;2:468. CrossrefGoogle Scholar

[21]

Paquot Y, Duport F, Smerieri A, et al. Optoelectronic reservoir computing. Sci Rep 2012;2:287. CrossrefGoogle Scholar

[22]

Larger L, Soriano MC, Brunner D, et al. Photonic information processing beyond turing: an optoelectronic implementation of reservoir computing. Opt Express 2012;20:3241–9. CrossrefGoogle Scholar

[23]

Duport F, Schneider B, Smerieri A, Haelterman M, Massar S. All-optical reservoir computing. Opt Express 2012;20: 22783–95. CrossrefGoogle Scholar

[24]

Brunner D, Fischer I. Reconfigurable semiconductor laser networks based on diffractive coupling. Opt lett 2015;40:3854. CrossrefGoogle Scholar

[25]

Dambre J, Verstraeten D, Schrauwen B, Massar S. Information processing capacity of dynamical systems. Sci Rep 2012;2:514. CrossrefGoogle Scholar

[26]

Sylvestre J. “Mechanical computations”, presentation at “BEYOND! von Neumann” workshop, Berlin May 18–20 (2016).

[27]

Caluwaerts K, D’Haene M, Verstraeten D, Schrauwen B. Locomotion without a brain: physical reservoir computing in tensegrity structures. Artif Life 2012;19:35–66. CrossrefGoogle Scholar

[28]

Hauser H, Ijspeert AJ, Füchslin RM, Pfeifer R, Maass W. Towards a theoretical foundation for morphological computation with compliant bodies. Biol Cybern 2011;105:355–70. CrossrefGoogle Scholar

[29]

Nakajima K, Li T, Hauser H, Pfeifer R. Exploiting short-term memory in soft body dynamics as a computational resource. J R Soc Interf 2014;11:20140437. CrossrefGoogle Scholar

[30]

Uchida A, Yoshimura K, Davis P, Yoshimori S, Roy R. Local conditional Lyapunov exponent characterization of consistency of dynamical response of the driven Lorenz system. Phys Rev E Stat Nonlin Soft Matter Phys 2008;78:036203. CrossrefGoogle Scholar

[31]

Oliver N. Consistency properties of a chaotic semiconductor laser driven by optical feedback. Phys Rev Lett 2015;114:123902. CrossrefGoogle Scholar

[32]

Soriano MC, Ortín S, Keuninckx L, et al. Delay-based reservoir computing: noise effects in a combined analog and digital implementation. IEEE Trans Neural Netw Learn Syst 2015;26:388–93. Google Scholar

[33]

Lukoševičius M, Jaeger H, Schrauwen B. Reservoir computing trends. KI Künstliche Intelligenz 2012;26:365–71. CrossrefGoogle Scholar

[34]

Simply silicon. Nat Photon 2010;4:491. Google Scholar

[35]

Vandoorne K, Dierckx W, Schrauwen B, et al. Toward optical signal processing using photonic reservoir computing. Opt Express 2008;16:11182. CrossrefGoogle Scholar

[36]

Vandoorne K, Dambre J, Verstraeten D, Schrauwen B, Bienstman P. Parallel reservoir computing using optical amplifiers. IEEE Trans Neural Netw 2011;22:1469–81. CrossrefGoogle Scholar

[37]

Salehi MR, Dehyadegari L. Optical signal processing using photonic reservoir computing. J Mod Opt 2014;61:144–5. CrossrefGoogle Scholar

[38]

Vandoorne K, Mechet P, Van Vaerenbergh T, et al. Experimental demonstration of reservoir computing on a silicon photonics chip. Nat Commun 2014;5:1–6. CrossrefGoogle Scholar

[39]

Barbay S, Kuszelewicz R, Yacomotti AM. Excitability in a semiconductor laser with saturable absorber. Opt Lett 2011;36:4476–8. CrossrefGoogle Scholar

[40]

Coomans W, Gelens L, Beri S, Danckaert J, Van der Sande G. Solitary and coupled semiconductor ring lasers as optical spiking neurons. Phys Rev E 2011;84:036209. CrossrefGoogle Scholar

[41]

Hurtado A, Schires K, Henning ID, Adams MJ. Investigation of vertical cavity surface emitting laser dynamics for neuromorphic photonic systems. Appl Phys Lett 2012;100. Paper number: 103703. CrossrefGoogle Scholar

[42]

Vaerenbergh TV, Fiers M, Mechet P, et al. Cascadable excitability in microrings. Opt Express 2012;20:20292–308. CrossrefGoogle Scholar

[43]

Nahmias MA, Tait AN, Shastri BJ, de Lima TF, Prucnal PR. Excitable laser processing network node in hybrid silicon: analysis and simulation. Opt Express 2015;23:26800–13. CrossrefGoogle Scholar

[44]

Shastri BJ, Nahmias MA, Tait AN, Rodriguez AW, Wu B, Prucnal PR. Spike processing with a graphene excitable laser. Sci Rep 2016;6:19126. CrossrefGoogle Scholar

[45]

Tait AN, Member S, Nahmias MA, Shastri BJ, Prucnal PR. Broadcast and weight: an integrated network for scalable photonic spike processing. J Lightwave Technol 2014;32:3427–39. CrossrefGoogle Scholar

[46]

Selmi F, Braive R, Beaudoin G, Sagnes I, Kuszelewicz R, Barbay S. Relative refractory period in an excitable semiconductor laser. Phys Rev Lett 2014;112:183902. CrossrefGoogle Scholar

[47]

Paquot Y, Dambre J, Schrauwen B, Haelterman M, Massar S. Reservoir computing: a photonic neural network for information processing,” in Proc. SPIE 7728, Nonlinear Optics and Applications IV 2010;7728:77280B–12. Google Scholar

[48]

Erneux T. Applied delayed differential equations. New York, Springer Science Business Media, 2009. Google Scholar

[49]

Soriano MC, Garca-Ojalvo J, Mirasso CR, Fischer I. Complex photonics: dynamics and applications of delay-coupled semiconductors lasers. Rev Mod Phys 2013;85:421–70. CrossrefGoogle Scholar

[50]

Argyris A, Syvridis D, Larger L, et al. Chaos-based communications at high bit rates using commercial fibre-optic links. Nature 2005;438:343–6. CrossrefGoogle Scholar

[51]

Uchida A, Amano K, Inoue M, et al. Fast physical random bit generation with chaotic semiconductor lasers. Nat Photon 2008;2:728–32. CrossrefGoogle Scholar

[52]

Appeltant L, Van der Sande G, Danckaert J, Fischer I. Constructing optimized binary masks for reservoir computing with delay systems. Sci Rep 2014;4:3629. CrossrefGoogle Scholar

[53]

Ikeda K, Daido H, Akimoto O. Optical turbulence: chaotic behavior of transmitted light from a ring cavity. Phys Rev Lett 1980;45:709. CrossrefGoogle Scholar

[54]

Goedgebuer J-P, Larger L, Porte H, Delorme F. Chaos in wavelength with a feedback tunable laser diode. Phys Rev E 1998;57:2795. CrossrefGoogle Scholar

[55]

Martinenghi R, Rybalko S, Jacquot M, Chembo YK, Larger L. Photonic nonlinear transient computing with multiple-delay wavelength dynamics. Phys Rev Lett 2012;108:244101. CrossrefGoogle Scholar

[56]

Soriano MC, Ortín S, Brunner D, et al. Optoelectronic reservoir computing: tackling noise-induced performance degradation. Opt Express 2013;21:12–20. CrossrefGoogle Scholar

[57]

Ortín S, Soriano MC, Pesquera L, et al. A unified framework for reservoir computing and extreme learning machines based on a single time-delayed neuron. Sci Rep 2015;5:14945. CrossrefGoogle Scholar

[58]

Duport F, Smerieri A, Akrout A, Haelterman M, Massar S. Fully analogue photonic reservoir computer. Sci Rep 2016;6:22381. CrossrefGoogle Scholar

[59]

Duport F, Smerieri A, Akrout A, Haelterman M, Massar S. Virtualization of a photonic reservoir computer. J Lightwave Technol 2016;34:2085–91. CrossrefGoogle Scholar

[60]

Lavrov R, Jacquot M, Larger L. Nonlocal nonlinear electro-optic phase dynamics demonstrating 10 Gb/s chaos communications. IEEE J Quantum Elect 2010;46:1430–5. CrossrefGoogle Scholar

[61]

Woods D, Naughton TJ. Optical computing: photonic neural networks. Nat Phys 2012;8:257–9. CrossrefGoogle Scholar

[62]

Soriano MC, Brunner D, Escalona-Morán M, Mirasso CR, Fischer I. Minimal approach to neuro-inspired information processing. Front Comput Neurosci 2015;9:68. CrossrefGoogle Scholar

[63]

Antonik P, Duport F, Smerieri A, Hermans M, Haelterman M, Massar S. Online training of an opto-electronic reservoir computer. In: Neural Information Processing. 1em plus 0.5em minus 0.4em Springer, 2015, pp. 233–240. Google Scholar

[64]

Huang G-B, Wang DH, Lan Y. Extreme learning machines: a survey. Int J Mach Learn Cyber 2011;2:107–22. CrossrefGoogle Scholar

[65]

Hermans M, Soriano MC, Dambre J, Bienstman P, Fischer I. Photonic delay systems as machine learning implementations. J Mach Learn Res 2015;16:2081–97. Google Scholar

[66]

Hermans M, Dambre J, Bienstman P. Optoelectronic systems trained with backpropagation through time. IEEE Trans Neural Netw Learn Syst 2015;26:1545–50. Google Scholar

[67]

Brunner D, Soriano MC, Mirasso CR, Fischer I. Parallel photonic information processing at gigabyte per second data rates using transient states. Nat Commun 2013;4:1364. CrossrefGoogle Scholar

[68]

Vinckier Q, Duport F, Smerieri A, et al. High-performance photonic reservoir computer based on a coherently driven passive cavity. Optica 2015;2:438–46. CrossrefGoogle Scholar

[69]

Brunner D, Soriano MC, Fischer I. High-speed optical vector and matrix operations using a semiconductor laser. IEEE Photonics Tech Lett 2013;25:1680–3. CrossrefGoogle Scholar

[70]

Hicke K, Escalona-Morán MA, Brunner D, Soriano MC, Fischer I, Mirasso CR. Information processing using transient dynamics of semiconductor lasers subject to delayed feedback. IEEE J Sel Top Quant 2013;19:1501610. CrossrefGoogle Scholar

[71]

Nakayama J, Kanno K, Uchida A. Laser dynamical reservoir computing with consistency: an approach of a chaos mask signal. Opt Express 2016;24:8679–92. CrossrefGoogle Scholar

[72]

Nguimdo RM, Verschaffelt G, Danckaert J, Van der Sande G. Fast photonic information processing using semiconductor lasers with delayed optical feedback: role of phase dynamics. Opt Express 2014;22:8672–86. CrossrefGoogle Scholar

[73]

Nguimdo RM, Verschaffelt G, Danckaert J, Van der Sande G. Simultaneous computation of two independent tasks using reservoir computing based on a single photonic nonlinear node with optical feedback. IEEE Trans Neural Netw Learn Syst 2015;26:3301–7. Google Scholar

[74]

Nguimdo RM, Verschaffelt G, Danckaert J, Van der Sande G. Reducing the phase sensitivity of laser-based optical reservoir computing systems. Opt Express 2016;24:1238–52. CrossrefGoogle Scholar

[75]

Dejonckheere A, Duport F, Smerieri A, et al. All-optical reservoir computer based on saturation of absorption. Opt Express 2014;22:10868–81. CrossrefGoogle Scholar

## Comments (0)

General note:By using the comment function on degruyter.com you agree to our Privacy Statement. A respectful treatment of one another is important to us. Therefore we would like to draw your attention to our House Rules.