2025/10/02 by Roberto Bernal-Arencibia, K. García Medina, Bernal-Arencibia, Roberto +5
Engineering · #Applied Physics (physics.app-ph) #FOS: Computer and information sciences #FOS: Physical sciences #Fatigue and fracture mechanics #Methodology (stat.ME) #Numerical methods in engineering #Welding Techniques and Residual Stresses
paper · pdf · doi:10.48550/arxiv.2510.01798
openalex publication_date 2025/10/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
The Eilers-Whittaker method for data smoothing effectiveness depends on the choice of the regularisation parameter, and automatic selection is a necessity for large datasets. Common methods, such as leave-one-out cross-validation, can perform poorly when serially correlated noise is present. We propose a novel procedure for selecting the control parameter based on the spectral entropy of the residuals. We define an S-curve from the Euclidean distance between points in a plot of the spectral entropy of the residuals versus that of the smoothed signal. The regularisation parameter corresponding to the absolute maximum of this S-curve is chosen as the optimal parameter. Using simulated data, we benchmarked our method against cross-validation and the V-curve. Validation was also performed on diverse experimental data. This robust and straightforward procedure can be a valuable addition to the available selection methods for the Eilers smoother.