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Updated: Jul 8, 2025

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尖端神经元泄漏和网络复发对基于事件的时空模式识别的影响

Mohamed Sadek Bouanane1, Dalila Cherifi1, Elisabetta Chicca2,3

  • 1Institute of Electrical and Electronic Engineering, University of Boumerdes, Boumerdes, Algeria.

Frontiers in neuroscience
|December 11, 2023
PubMed
概括

尖端神经网络从神经泄漏中受益,特别是在时间数据和网络复发方面,提高了高效神经形态硬件的准确性. 泄漏并不总是增加尖峰稀疏性,但可以通过异质性提高性能.

关键词:
数字神经形态架构的数字神经形态架构.基于事件的传感器.网络的复发是网络的复发.神经异质性的神经异质性神经元的泄漏 泄漏的神经元的泄漏时间空间的模式.刺激神经网络的神经网络.

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