Sparse-firing regularization methods for spiking neural networks with time-to-first-spike coding

Yusuke Sakemi; Kakei Yamamoto; Takeo Hosomi; Kazuyuki Aihara

doi:10.1038/s41598-023-50201-5

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Sparse-firing regularization methods for spiking neural networks with time-to-first-spike coding

Yusuke Sakemi Kakei Yamamoto Takeo Hosomi Kazuyuki Aihara

Year: 2023 Journal: Scientific Reports Vol: 13 (1)Pages: 22897-22897 Publisher: Nature Portfolio

DOI: 10.1038/s41598-023-50201-5

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Keywords:

MNIST database Computer science Neural coding Backpropagation Spiking neural network Artificial neural network Artificial intelligence Multilayer perceptron Pattern recognition (psychology) Coding (social sciences) Regularization (linguistics) Convolutional neural network Spike (software development) Mathematics

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Advanced Memory and Neural Computing

Physical Sciences → Engineering → Electrical and Electronic Engineering

Neural dynamics and brain function

Life Sciences → Neuroscience → Cognitive Neuroscience

Neural Networks and Reservoir Computing

Physical Sciences → Computer Science → Artificial Intelligence

Sparse-firing regularization methods for spiking neural networks with time-to-first-spike coding

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