Order of approximation for nonlinear sampling Kantorovich operators in Orlicz spaces

Neural network operators: Constructive interpolation of multivariate functions

“…Moreover, also not necessarily continuous signals can be reconstructed. In this case, sampling operators of the Kantorovich type seems to be the most appropriate to perform this task, see, e.g., [9,33,34,22,23,35,36,37]. As showed in Remark 2.1, the density functions φ s (x) dened in this paper satisfy all the typical properties of the approximate identities and then, can be used as kernels in the above sampling operators in the univariate case.…”

Multivariate sampling Kantorovich operators: from the theory to the Digital Image Processing algorithm

“…[10,11,13,14]). Examples of one-dimensional kernels are the well-known Fejér's kernel, i.e., F (x) = , and many others, see e.g., [2,7,8].…”

“…Here, we present the theory and some applications to Digital Image Processing (D.I.P.) of the multivariate sampling Kantorovich operators (see e.g., [2,6,8]), defined by:…”

Applications of Approximation Theory to thermographic images in earthquake engineering

“…The sampling Kantorovich operators have been introduced in a multivariate setting to approximate and reconstruct not necessarily continuous signals/images, (see e.g., [1][2][3][4]). In this work we consider the multivariate sampling Kantorovich operators defined by:…”