AVERAGE SAMPLING IN MIXED SHIFT-INVARIANT SUBSPACES WITH GENERATORS IN A HYBRID-NORM SPACE
This paper mainly studies the average sampling and reconstruction in shift-invariant subspaces of mixed Lebesgue spaces where the generator φ of the shift-invariant subspace belongs to a hybrid-norm space of mixed form, which is weaker than the usual assumption of Wiener amalgam space and allows to control the orders p, q. First, the sampling stability for two kinds of average sampling functionals is established. Then, we give the corresponding iterative approximation projection algorithms with exponential convergence for reconstructing signals in the mixed shift-invariant subspaces from the average samples.
average sampling, shift-invariant signal, mixed Lebesgue space, hybrid-norm.
Received: April 8, 2022; Accepted: May 25, 2022; Published: June 14, 2022
How to cite this article: Haizhen Li and Yan Tang, Average sampling in mixed shift-invariant subspaces with generators in a hybrid-norm space, Far East Journal of Applied Mathematics 113 (2022), 45-66. http://dx.doi.org/10.17654/0972096022010
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