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Pattern classification based on a multi-spike learning algorithm in a photonic spiking neural network with VCSEL-SA
In this paper, we propose a pattern classification method based on the modified multi-spike Tempotron-like ReSuMe algorithm in a VCSEL-SA-based photonic spiking neuron network. Based on the multi-spike triggering mechanism, the proposed method can capture the global information to overcome the limitation of the traditional single-spike triggering algorithm, which can be used to effectively process more complex temporal information tasks, accompanied by good robustness to noise.
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