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Proceedings Paper

The optimum estimation of statistical signals based on systematic expression of many types of sample arrays in multidimensional space
Author(s): Yuichi Kida; Takuro Kida
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Paper Abstract

Extended interpolatory approximation is discussed for some classes of n-dimensional statistical signals. Firstly, we present two sufficient conditions of the optimum approximation. Then, as example of this optimum approximation, we consider approximation of n-dimensional statistical signals expressed by linear combination of the finite set of base signals in a n-dimensional space. We assume that these signals have generalized mutual moment smaller than a given positive number. Related topic was discussed in the previous paper. However, discrete running approximation along the time axis that uses shift-invariant interpolation functions with the finite supports is not treated in the previous paper. In the final part of this paper, we discuss best running approximation of n-dimensional signals expressed by linear combination of the finite set of sinusoidal signals in a n-dimensional space. The presented methods have the minimum measure of approximation error among all the linear and the nonlinear approximations using the same measure of error and generalized sample values.

Paper Details

Date Published: 25 August 2006
PDF: 12 pages
Proc. SPIE 6315, Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications IX, 63150C (25 August 2006); doi: 10.1117/12.681945
Show Author Affiliations
Yuichi Kida, Ohu Univ. (Japan)
Takuro Kida, Nihon Univ. (Japan)


Published in SPIE Proceedings Vol. 6315:
Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications IX
Gerhard X. Ritter; Mark S. Schmalz; Junior Barrera; Jaakko T. Astola, Editor(s)

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