Smooth Signal Activity Detection in White Gaussian Noise: Application to P300 Detection

Signal activity detection is an important problem in many fields of study, including communication, radar, and biomedical signal processing. As we know, many signals have a smooth template compared to noise. In this work, this extra info on the signal structure is used to improve conventional signal detection methods. The suggested method is applied to a P300 dataset to detect this template in background electroencephalography. The results demonstrate the effectiveness of the method in low signal-to-noise ratios.