Advances in photonic reservoir computing

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Selmi, 2014, Relative refractory period in an excitable semiconductor laser, Phys Rev Lett, 112, 183902, 10.1103/PhysRevLett.112.183902

Soriano, 2013, Optoelectronic reservoir computing : tackling noise - induced performance degradation, Opt Express, 21, 12, 10.1364/OE.21.000012

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Soriano, 2015, Delay - based reservoir computing : noise effects in a combined analog and digital implementation Neural Netw Learn, IEEE Trans Syst, 26, 388

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Nguimdo, 2015, der Simultaneous computation of two independent tasks using reservoir computing based on a single photonic nonlinear node with optical feedback Neural Netw Learn, IEEE Trans Syst, 26, 3301

Martinenghi, 2012, Photonic nonlinear transient computing with multiple - delay wavelength dynamics, Phys Rev Lett, 108, 244101, 10.1103/PhysRevLett.108.244101

Brunner, 2013, Parallel photonic information processing at gigabyte per second data rates using transient states, Nat Commun, 4, 1364, 10.1038/ncomms2368

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Brunner, 2013, High - speed optical vector and matrix operations using a semiconductor laser, IEEE Photonics Tech Lett, 25, 1680, 10.1109/LPT.2013.2273373

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Vandoorne, 2014, Experimental demonstration of reservoir computing on a silicon photonics chip, Nat Commun, 5, 1, 10.1038/ncomms4541

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Shastri, 2016, Spike processing with a graphene excitable laser, Sci Rep, 6, 19126, 10.1038/srep19126

Nakajima, 2014, Exploiting short - term memory in soft body dynamics as a computational resource, Soc Interf, 11, 20140437, 10.1098/rsif.2014.0437

Soriano, 2013, Complex photonics : dynamics and applications of delay - coupled semiconductors lasers, Rev Mod Phys, 85, 421, 10.1103/RevModPhys.85.421

Vandoorne, 2011, Parallel reservoir computing using optical amplifiers, IEEE Trans Neural Netw, 22, 1469, 10.1109/TNN.2011.2161771

Soriano, 2015, Minimal approach to neuro - inspired information processing, Front Comput Neurosci, 9, 68, 10.3389/fncom.2015.00068

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Duport, 2016, Fully analogue photonic reservoir computer, Sci Rep, 6, 22381, 10.1038/srep22381

Caluwaerts, 2012, Locomotion without a brain : physical reservoir computing in tensegrity structures, Artif Life, 19, 35, 10.1162/ARTL_a_00080

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Brunner, 2015, Reconfigurable semiconductor laser networks based on diffractive coupling, Opt lett, 40, 3854, 10.1364/OL.40.003854

Duport, 2016, Virtualization of a photonic reservoir computer, J Lightwave Technol, 34, 2085, 10.1109/JLT.2016.2524559

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Dejonckheere, 2014, All - optical reservoir computer based on saturation of absorption, Opt Express, 22, 10868, 10.1364/OE.22.010868

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Nakayama, 2016, Laser dynamical reservoir computing with consistency : an approach of a chaos mask signal, Opt Express, 24, 8679, 10.1364/OE.24.008679

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Barbay, 2011, Excitability in a semiconductor laser with saturable absorber, Opt Lett, 36, 4476, 10.1364/OL.36.004476

Tait, 2014, Broadcast and weight : an integrated network for scalable photonic spike processing, J Lightwave Technol, 32, 3427, 10.1109/JLT.2014.2345652

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Vaerenbergh, 2012, Cascadable excitability in microrings, Opt Express, 20, 20292, 10.1364/OE.20.020292

Nguimdo, 2016, der Reducing the phase sensitivity of laser - based optical reservoir computing systems, Opt Express, 24, 1238, 10.1364/OE.24.001238

Lavrov, 2010, Nonlocal nonlinear electro - optic phase dynamics demonstrating Gb / s chaos communications, IEEE J Quantum Elect, 46, 1430, 10.1109/JQE.2010.2049987

Uchida, 2008, Fast physical random bit generation with chaotic semiconductor lasers, Nat Photon, 2, 728, 10.1038/nphoton.2008.227

Paquot, 2012, Optoelectronic reservoir computing, Sci Rep, 2, 287, 10.1038/srep00287

Hicke, 2013, Information processing using transient dynamics of semiconductor lasers subject to delayed feedback, IEEE J Sel Top Quant, 19, 1501610, 10.1109/JSTQE.2013.2241738

Nahmias, 2015, Excitable laser processing network node in hybrid silicon : analysis and simulation, Opt Express, 23, 26800, 10.1364/OE.23.026800

Verstraeten, 2007, An experimental unification of reservoir computing methods, Neural Networks, 20, 391, 10.1016/j.neunet.2007.04.003

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Oliver, 2015, Consistency properties of a chaotic semiconductor laser driven by optical feedback, Phys Rev Lett, 114, 123902, 10.1103/PhysRevLett.114.123902

Vandoorne, 2008, Toward optical signal processing using photonic reservoir computing, Opt Express, 16, 11182, 10.1364/OE.16.011182

Uchida, 2008, Local conditional Lyapunov exponent characterization of consistency of dynamical response of the driven Lorenz system, Phys Rev E Stat Nonlin Soft Matter Phys, 78, 036203, 10.1103/PhysRevE.78.036203

Appeltant, 2014, der Constructing optimized binary masks for reservoir computing with delay systems, Sci Rep, 4, 3629, 10.1038/srep03629

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Larger, 2012, Photonic information processing beyond turing : an optoelectronic implementation of reservoir computing, Opt Express, 20, 3241, 10.1364/OE.20.003241

Jaeger, 2004, Harnessing nonlinearity : predicting chaotic systems and saving energy in wireless communication, Science, 304, 78, 10.1126/science.1091277

Duport, 2012, All - optical reservoir computing, Opt Express, 20, 22783, 10.1364/OE.20.022783

Salehi, 2014, Optical signal processing using photonic reservoir computing, J Mod Opt, 61, 144, 10.1080/09500340.2014.940017

Woods, 2012, Optical computing : photonic neural networks, Nat Phys, 8, 257, 10.1038/nphys2283

Appeltant, 2011, der Information processing using a single dynamical node as complex system, Nat Commun, 2, 468, 10.1038/ncomms1476

Ortín, 2015, A unified framework for reservoir computing and extreme learning machines based on a single time - delayed neuron, Sci Rep, 5, 14945, 10.1038/srep14945

Hermans, 2015, Photonic delay systems as machine learning implementations, J Mach Learn Res, 16, 2081