A Gaussian regularization for derivative sampling interpolation of signals in the linear canonical transform representations

Abstract The linear canonical transform (LCT) plays an important role in signal and image processing from both theoretical practical points of view. Various sampling representations for band-limited non-band-limited signals the LCT domain have been established. We focus this paper on derivative reconstruction, where reconstruction procedure utilizes samples its first derivative. Our major aim was to incorporate operator with a Gaussian regularization kernel, which one hand is applicable not necessarily other hastens convergence procedure. amplitude error also considered deriving rigorous estimates. obtained results are tested through various simulated experiments.