Beyond the Noise: Smarter Signal Detection with Machine Learning
![A transformation utilizing the score function maximizes the local Fisher information, enabling a detector-applied to the transformed data-to achieve a higher probability of detection, though estimates remain biased globally, while application to the original data yields globally unbiased estimates with a variance exceeding the Cramér-Rao lower bound [latex] CRLB [/latex].](https://arxiv.org/html/2603.01737v1/2603.01737v1/x2.png)
A new approach leverages neural networks to dramatically improve the detection of faint signals buried in complex, non-Gaussian noise.
![A transformation utilizing the score function maximizes the local Fisher information, enabling a detector-applied to the transformed data-to achieve a higher probability of detection, though estimates remain biased globally, while application to the original data yields globally unbiased estimates with a variance exceeding the Cramér-Rao lower bound [latex] CRLB [/latex].](https://arxiv.org/html/2603.01737v1/2603.01737v1/x2.png)
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