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cs.NE2025
Lightweight LIF-only SNN accelerator using differential time encoding
Daniel Windhager, Lothar Ratschbacher, Bernhard A. Moser +1
Spiking Neural Networks (SNNs) offer a promising solution to the problem of increasing computational and energy requirements for modern Machine Learning (ML) applications. Due to t…
cs.NE2025
Spiking Neural Network Accelerator Architecture for Differential-Time Representation using Learned Encoding
Daniel Windhager, Lothar Ratschbacher, Bernhard A. Moser +1
Spiking Neural Networks (SNNs) have garnered attention over recent years due to their increased energy efficiency and advantages in terms of operational complexity compared to trad…
cs.NE2024
On the Solvability of the {XOR} Problem by Spiking Neural Networks
Bernhard A. Moser, Michael Lunglmayr
The linearly inseparable XOR problem and the related problem of representing binary logical gates is revisited from the point of view of temporal encoding and its solvability by sp…