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Theoretical investigation of weight-dependent optical spike timing dependent plasticity based on VCSOA
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Abstract
We propose an implement scheme of the weight-dependent optical spike timing dependent plasticity (STDP) based on the vertical-cavity semiconductor optical amplifiers (VCSOAs) subject to double optical spike injections, and numerically investigate the effects of the internal and external parameters of VCSOAs on the optical STDP curve by the well-known Fabry-Pérot approach. Additionally, the optical weight-dependent STDP is realized by introducing the various bias current according to the feedback signal. The simulation results show that, the width and height of the optical STDP curve window can be effectively controlled by adjusting the relevant parameters of VCSOAs. Moreover, the optical weight-dependent STDP is analogous to the biological STDP synapses and can be used to balance the stability and competition among synapses. These results can offer great potential for constructing a large-scale energy efficient optical spiking neural networks (SNNs).
Title: Theoretical investigation of weight-dependent optical spike timing dependent plasticity based on VCSOA
Description:
Abstract
We propose an implement scheme of the weight-dependent optical spike timing dependent plasticity (STDP) based on the vertical-cavity semiconductor optical amplifiers (VCSOAs) subject to double optical spike injections, and numerically investigate the effects of the internal and external parameters of VCSOAs on the optical STDP curve by the well-known Fabry-Pérot approach.
Additionally, the optical weight-dependent STDP is realized by introducing the various bias current according to the feedback signal.
The simulation results show that, the width and height of the optical STDP curve window can be effectively controlled by adjusting the relevant parameters of VCSOAs.
Moreover, the optical weight-dependent STDP is analogous to the biological STDP synapses and can be used to balance the stability and competition among synapses.
These results can offer great potential for constructing a large-scale energy efficient optical spiking neural networks (SNNs).
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