Training Deep Spiking Neural Networks Using Backpropagation
نویسندگان
چکیده
منابع مشابه
Training Deep Spiking Neural Networks Using Backpropagation
Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signa...
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Compared with artificial neural networks (ANNs), spiking neural networks (SNNs) are promising to explore the brain-like behaviors since the spikes could encode more spatiotemporal information. Although existing schemes including pretraining from ANN or direct training based on backpropagation (BP) make the supervised training of SNNs possible, these methods only exploit the networks’ spatial do...
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ژورنال
عنوان ژورنال: Frontiers in Neuroscience
سال: 2016
ISSN: 1662-453X
DOI: 10.3389/fnins.2016.00508