[1] [1] Liu Dawei, Han Ling, Han Xiaoyong. High spatial resolution remote sensing image classification based on deep learning［J］. Acta Optica Sinica, 2016, 36(4): 0428001.

[2] [2] Merolla P A, Arthur J V, Alvarez-Icaza R, et al. A million spiking-neuron integrated circuit with a scalable communication network and interface［J］. Science, 2014, 345(6197): 668-673.

[3] [3] Benjamin B V, Gao P R, Mcquinn E, et al. Neurogrid: A mixed-analog-digital multichip system for large-scale neural simulations［C］. Proc IEEE, 2014, 102(5): 699-716.

[4] [4] Schemmel J,Brüderle D, Grübl A, et al. A wafer-scale neuromorphic hardware system for large-scale neural modeling［C］. Proc IEEE Int Symp Circuits Syst, 2010: 1947-1950.

[5] [5] Maass W. Networks of spiking neurons: The third generation of neural network models［J］. Neural Networks, 1997, 10(9): 1659-1671.

[6] [6] Kravtsov K S, Fok M P, Prucnal P R, et al. Ultrafast all-optical implementation of a leaky integrate-and-fire neuron［J］. Opt Express, 2011, 19(3): 2133-2147.

[7] [7] Fok M P, Deming H, Nahmias M, et al. Signal feature recognition based on lightwave neuromorphic signal processing［J］. Opt Lett, 2011, 36(1): 19-21.

[8] [8] Hurtado A, Schires K, Henning I D, et al. Investigation of vertical cavity surface emitting laser dynamics for neuromorphic photonic systems［J］. Appl Phys Lett, 2012, 100(10): 103703.

[9] [9] Turconi M, Garbin B, Feyereisen M, et al. Control of excitable pulses in an injection-locked semiconductor laser［J］. Phys Rev E, 2013, 88(2): 022923.

[10] [10] Vaerenbergh T V, Fiers M, Mechet P, et al. Cascadable excitability in microrings［J］. Opt Express, 2012, 20(18): 20292-20308.

[11] [11] Alexander K,Vaerenbergh T V, Fiers M, et al. Excitability in optically injected microdisk lasers with phase controlled excitatory and inhibitory response［J］. Opt Express, 2013, 21(22): 26182-26191.

[12] [12] Gholipour B, Bastock P, Craig C, et al. Amorphous metal-sulphide microfibers enable photonic synapses for brain-like computing［J］. Adv Opt Mater, 2015, 3(5): 635-641.

[13] [13] Shastri B J, Nahmias M A, Tait A N, et al. Spike processing with a graphene excitable laser［J］. Sci Rep-UK, 2016, 6: 19126.

[14] [14] Tzounopoulos T, Kim Y, Oertel D, et al. Cell-specific, spike timing-dependent plasticities in the dorsal cochlear nucleus［J］. Nat Neurosci, 2004, 7(7): 719-725.

[15] [15] Caporale N, Dan Y. Spike timing-dependent plasticity: a Hebbian learning rule［J］. Annu Rev Neurosci, 2008, 31: 25-46.

[16] [16] Xie X H, Seung H S. Spike-based learning rules and stabilization of persistent neural activity［J］. Adv Neural Inf Process Syst, 2000, 12: 199-208.

[17] [17] Fok M P, Tian Y, Rosenbluth D, et al. Pulse lead/lag timing detection for adaptive feedback and control based on optical spike-timing-dependent plasticity［J］. Opt Lett, 2013, 38(4): 419-421.

[18] [18] Toole R, Tait A N, Ferreira D L T, et al. Photonic implementation of spike timing dependent plasticity and learning algorithms of biological neural systems［J］. J Lightwave Technol, 2016, 34(2): 470-476.

[19] [19] Ren Q S, Zhang Y L, Wang R, et al. Optical spike-timing-dependent plasticity with weight-dependent learning window and reward modulation［J］. Opt Express, 2015, 23(19): 25247-25258.

[20] [20] Li Q, Wang Z, Le Y S, et al. Optical implementation of neural learning algorithms based on cross-gain modulation in a semiconductor optical amplifier［C］. SPIE, 2016, 10019: 100190E.

[21] [21] Luz Y, Shamir M. Balancing feed-forward excitation and inhibition via Hebbian inhibitory synaptic plasticity［J］. Plos Comput Biol. 2012, 8(1): e1002334.

[22] [22] Zamarreo-Ramos C, Camuas-Mesa L A, Pérez-Carrasco J A, et al. On spike-timing-dependent-plasticity, memristive devices, and building a self-learning visual cortex［J］. Front Neurosci, 2011, 5: 1-22.