Parameter-Efficient Time–Frequency Temporal Convolution with Log-Percentile Normalization for Underwater Acoustic MAC Protocol Recognition
This study evaluates a parameter-efficient time–frequency temporal convolutional network (RTF-TCN) using exclusively simulated clean waveforms corrupted by independently generated Gaussian or symmetric alpha-stable noise and the results support parameter efficiency within the tested conditions, but they do not establis...