Computer Science – Information Theory
Scientific paper
2007-07-02
Sampl. Theory Signal Image Process., Vol. 8, No. 2, May 2009, pp. 127-146
Computer Science
Information Theory
20 pages, extended version of talk at International Workshop on Sampling Theory and Applications SampTA07, Thessaloniki, Greec
Scientific paper
A generalized sampling theorem for frequency localized signals is presented. The generalization in the proposed model of sampling is twofold: (1) It applies to various prefilters effecting a "soft" bandlimitation, (2) an approximate reconstruction from sample values rather than a perfect one is obtained (though the former might be "practically perfect" in many cases). For an arbitrary finite-energy signal the frequency localization is performed by a prefilter realizing a crosscorrelation with a function of prescribed properties. The range of the filter, the so-called localization space, is described in some detail. Regular sampling is applied and a reconstruction formula is given. For the reconstruction error a general error estimate is derived and connections between a critical sampling interval and notions of "soft bandwidth" for the prefilter are indicated. Examples based on the sinc-function, Gaussian functions and B-splines are discussed.
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