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6 papers
Quantitative estimates for nonlinear sampling Kantorovich operators
Nursel Cetin, Danilo Costarelli, Gianluca Vinti
In this paper, we establish quantitative estimates for nonlinear sampling Kantorovich operators in terms of the modulus of continuity in the setting of Orlicz spaces. This general…
Convergence in variation for the multidimensional generalized sampling series and applications to smoothing for digital image processing
Laura Angeloni, Danilo Costarelli, Gianluca Vinti
In this paper we study the problem of the convergence in variation for the generalized sampling series based upon averaged-type kernels in the multidimensional setting. As a crucia…
Convergence in Orlicz spaces by means of the multivariate max-product neural network operators of the Kantorovich type and applications
Danilo Costarelli, Anna Rita Sambucini, Gianluca Vinti
In this paper, convergence results in a multivariate setting have been proved for a family of neural network operators of the max-product type. In particular, the coefficients expr…
An inverse result of approximation by sampling Kantorovich series
D. Costarelli, G. Vinti
In the present paper, an inverse result of approximation, i.e., a saturation theorem for the sampling Kantorovich operators is derived, in the case of uniform approximation for uni…
A general approximation approach for the simultaneous treatment of integral and discrete operators
Gianluca Vinti, Luca Zampogni
In this paper we give a unitary approach for the simultaneous study of the convergence of discrete and integral operators described by means of a family of linear continuous functi…
A characterization of the convergence in variation for the generalized sampling series
Laura Angeloni, Danilo Costarelli, Gianluca Vinti
In this paper, we study the convergence in variation for the generalized sampling operators based upon averaged-type kernels and we obtain a characterization of absolutely continuo…