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A. Castagnetti

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Open access Oct 2026

Beyond binary SNNs: a hardware-algorithm co-design and architectural evaluation for graded spike networks

While Spiking Neural Networks offer a promising path toward energy-efficient edge intelligence, conventional Binary representations often suffer from high inference latency and discretization errors. Multi-level (graded) spike models address these limitations by increasing information density per pulse, yet they typi...

Wen-Fei Song, Andrea Castagnetti, Pierre-Emmanuel Novac et al. · 0 citations
Open access 2026

A Hardware-Aware Analysis of Energy Efficiency and Quantization Trade-Offs in Spiking Neural Networks

An in depth analysis of the different trade-offs between quantization, generalization performance, and energy efficiency between binary SNNs, multi-level SNNs and ANNs for two different applications scenarios: image classification and image denoising and results show that multi-level spiking neurons provide better info...

Andrea Castagnetti, Alain Pegatoquet, Benoît Miramond · 0 citations

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