# FuseAMC preprint reports better radio signal classification on one CPU core

_Published Thursday, November 5, 2026 at 12:12 AM EST · Science, AI · Latest · Tier 2 — Notable_

Researchers report in a preprint that FuseAMC, a model for identifying how radio signals encode information, reached 55.8% overall accuracy on RadioML 2016.10a while training and running on one CPU core. It improved on the best cumulant-feature baseline by 5.1 points and on a convolutional neural network alone by 3.2 points.

The system combines a neural network's predictions with those of a classifier using statistical signal features. The network handles noisier signals better, while the statistical classifier performs better on cleaner signals. Tested across 5 seeds on a 44k-frame held-out test set, the pipeline requires roughly 3 MFLOPs per frame; the reported gains concern that benchmark.

## Sources

- [cs.LG updates on arXiv.org](https://arxiv.org/abs/2611.05937)

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Canonical: https://techandbusiness.org/newswire/TsucleFNP4_v95-cR3QBdt
Published: 2026-11-05T05:12:06.375Z
Story chronology: 2026-11-05T05:00:00.000Z
Retrieved: 2026-11-05T07:42:53.833Z
Publisher: Tech & Business (techandbusiness.org)