Semi-Average Sampling for Shift-Invariant Signals in a Mixed Lebesgue Space. (3rd July 2020)

• Record Type: Journal Article
• Authors: Jiang, Yingchun; Kou, Junke
• Is Part Of: Numerical functional analysis and optimization. Volume 41:Number 9(2020)
• Page Start: 1045
• Page End: 1064
• Publication Date: 2020-07-03
• Subjects: Mixed hybrid-norm -- mixed Lebesgue space -- semi-average sampling -- shift-invariant subspace; 94A20 -- 46E30; Functional analysis -- Periodicals; Numerical analysis -- Periodicals; Mathematical optimization -- Periodicals; Numerical Analysis, Computer-Assisted; 515.705
• DOI: 10.1080/01630563.2020.1737815
• Languages: English
• ISSNs: 0163-0563

Abstract

Abstract: This article mainly studies the nonuniform and semi-average sampling of time-varying shift-invariant signals living in a mixed Lebesgue space L p, q ( R d + 1 ), under the condition that the generator φ of the shift-invariant subspace belongs to a hybrid-norm space of mixed form depending on the orders p and q . First, the sampling stability for two kinds of semi-average sampling functionals is established. Then, we give the corresponding iterative approximation projection algorithms with exponential convergence for recovering the time-based shift-invariant signals from the semi-average samples.