DocumentCode
2245045
Title
Linear approach to the least-squares multidimensional polynomial fitting
Author
Deng, Tian-Bo
Author_Institution
Dept. of Inf. Sci., Toho Univ., Funabashi, Japan
Volume
3
fYear
1997
fDate
9-12 Sep 1997
Firstpage
1288
Abstract
It is well known that the least-squares one-dimensional (1-D) polynomial fitting problem is linear. However, multidimensional (M-D) polynomial fitting is often treated as a nonlinear problem. This paper shows that the least-squares M-D polynomial fitting problem is also a linear problem, and proposes a linear method for solving it. Two fitting examples in the 2-D case are given to illustrate the effectiveness of the proposed method
Keywords
filtering theory; least squares approximations; multidimensional digital filters; polynomials; data interpolation; digital filters; least-squares multidimensional polynomial fitting; linear problem; linear solution method; optimal coefficients; variable filter design; Approximation algorithms; Approximation error; Differential equations; Digital filters; Frequency; Minimization methods; Multidimensional systems; Polynomials; Sampling methods; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Information, Communications and Signal Processing, 1997. ICICS., Proceedings of 1997 International Conference on
Print_ISBN
0-7803-3676-3
Type
conf
DOI
10.1109/ICICS.1997.652195
Filename
652195
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