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Optimal representation of multivariate functions or data in visualizable low-dimensional spaces 被引量:1

Optimal representation of multivariate functions or data in visualizable low-dimensional spaces
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摘要 It is intended to find the best representation of high-dimensional functions or multivariate data in L2(W) with fewest number of terms, each of them is a combination of one-variable function. A system of nonlinear integral equations has been derived as an eigenvalue problem of gradient operator in the said space. It proved that the complete set of eigenfunctions generated by the gradient operator constitutes anorthonormal system, and any function of L2(W) can beexpanded with fewest terms and exponential rapidity of convergence. It is also proved as a corollary, thegreatest eigenvalue of the integral operators hasmultiplicity 1 if the dimension of the underlying space nn = 2, 4 and 6. It is intended to find the best representation of high-dimensional functions or multivariate data in L2(W) with fewest number of terms, each of them is a combination of one-variable function. A system of nonlinear integral equations has been derived as an eigenvalue problem of gradient operator in the said space. It proved that the complete set of eigenfunctions generated by the gradient operator constitutes anorthonormal system, and any function of L2(W) can beexpanded with fewest terms and exponential rapidity of convergence. It is also proved as a corollary, thegreatest eigenvalue of the integral operators hasmultiplicity 1 if the dimension of the underlying space nn = 2, 4 and 6.
出处 《Chinese Science Bulletin》 SCIE EI CAS 2001年第16期1337-1345,共9页
关键词 nonlinear integral equations gradient OPERATORS EIGENVALUES orthonormal system of EIGENFUNCTIONS OPTIMAL approximation. nonlinear integral equations, gradient operators,eigenvalues, orthonormal system of eigenfunctions, optimal approximation.
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