Abstract:Recent studies have shown that convolutional neural networks (CNNs) are not the only feasible solution for image classification. Furthermore, weight sharing and backpropagation used in CNNs do not correspond to the mechanisms present in the primate visual system. To propose a more biologically plausible solution, we designed a locally connected spiking neural network (SNN) trained using spike-timingdependent plasticity (STDP) and its reward-modulated variant (R-STDP) learning rules. The use of spiking neurons … Show more
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