Details

Title

A Reconstruction Method of Generalized Sampling Based on Generalized Inverse

Journal title

Metrology and Measurement Systems

Yearbook

2010

Issue

No 2

Authors

Keywords

Hilbert spaces ; generalized sampling ; reconstruction ; generalized inverse

Divisions of PAS

Nauki Techniczne

Publisher

Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation

Date

2010

Type

Artykuły / Articles

Identifier

DOI: 10.2478/v10178-010-0015-7 ; ISSN 2080-9050, e-ISSN 2300-1941

Source

Metrology and Measurement Systems; 2010; No 2

Pages

163-172

References

Papoulis A. (1977), Generalized sampling expansion, IEEE Trans. Circuits Syst, 24, 652. ; Unser M. (1994), A general sampling theory for nonideal acquisition devices, IEEE Trans. Signal Process, 42, 2915. ; S. Chang Eon (2008), Nonuniform Sampling of Bandlimited Functions, IEEE Trans. Informat. Theory, 54, 7, 3814. ; Unser M. (1999), Splines: A perfect fit for signal and image processing, IEEE Signal Process. Mag, 22. ; Eldar Y. (2006), Non-ideal sampling and interpolation from noisy observations in shift-invariant spaces, IEEE Trans. Signal Process, 54, 7, 2636. ; Remani S. (2008), Nonideal Sampling and Regularization Theory, IEEE Trans. Signal Process, 56, 3, 1055. ; Eldar Y. (2003), Sampling and reconstruction in arbitrary spaces and oblique dual frame vectors, J. Fourier Anal. Appl, 1, 9, 77. ; Vaidyanathan P. (2001), Generalizations of the sampling theorem: Seven decades after Nyquist, IEEE Trans. Circuit Syst. I. Fundam. Theory Appl, 48, 9, 1094. ; M. Lu Yue (2008), A Theory for Sampling Signals From a Union of Subspaces, IEEE Trans. Signal Process, 56, 6, 2334. ; Djokovic I. (1997), Generalized sampling theorems in multiresolution subspaces, IEEE Trans. Signal Process, 45, 583. ; Zhaoxuan Z. (2009), Computation of reconstruction function for samples in shift-invariant spaces, Mertol. Meas. Syst, 16, 4, 535. ; Eldar Y. (2004), Sampling, Wavelets and Tomography, 3360.

Open Access Policy

Metrology and Measurement Systems is an open access journal with all content available with no charge in full text version.


The journal content is available under the license CC BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/
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