ATW-SNN: low-accuracy-loss asymmetric ternary-weight spiking neural network with spike calibration strategy

The deployment of spiking neural networks (SNNs) on resource-constrained devices is mainly limited by memory footprint and energy consumption. Specifically, these limitations stem from the overhead incurred by full-precision storage and floating-point operations. To address these bottlenecks, we pro...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Yihang Chen, Haoran Gao, Yingcheng Lin, Cong Shi
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	IOP Publishing 2026-01-01
Sarja:	Neuromorphic Computing and Engineering
Aiheet:	spiking neural network (SNN) ternary weights model compression asymmetric quantization knowledge distillation
Linkit:	https://doi.org/10.1088/2634-4386/ae379b
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