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Nonlinear interpolation and norm minimization

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Abstract

We prove that the set of convolution-type functions in ℝ d that satisfy the interpolation conditions contains a unique function whose convolution element has the minimumL p -norm. The extremal function is determined by solving a nonlinear interpolation problem. The results are applied to an operator recovery problem.

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References

  1. J. C. Holladay, “Smoothest curve approximation,”Math. Tables Aids Comput.,11, 233–243 (1957).

    MATH  MathSciNet  Google Scholar 

  2. S. Karlin, “Some variational problems on certain Sobolev spaces and perfect splines,”Bull. Amer. Math. Soc.,79, No. 1, 124–128 (1973).

    MATH  MathSciNet  Google Scholar 

  3. S. D. Fisher and J. W. Jerome, “The existence, characterization and essential uniqueness of solutions ofL extremal problems,”Trans. Amer. Math. Soc.,187, 391–404 (1974).

    MathSciNet  Google Scholar 

  4. S. D. Fisher and J. W. Jerome, “Spline solutions ofL 1 extremal problems in one and several variables,”J. Approx. Theory,13, 73–83 (1975).

    Article  MathSciNet  Google Scholar 

  5. M. Golomb, “H m,p-extensions byH m,p-splines,”J. Approx. Theory,5, 238–275 (1972).

    Article  MATH  MathSciNet  Google Scholar 

  6. J. Ahlberg, E. Nilson, and J. Walsh,The Theory of Splines and their Applications, Academic Press, London (1967).

    Google Scholar 

  7. S. B. Stechkin and Yu. N. Subbotin,Splines in Numerical Analysis [in Russian], Nauka, Moscow (1976).

    Google Scholar 

  8. P.-J. Laurent,Approximation et optimisation, Dunod, Paris (1972).

    Google Scholar 

  9. V. A. Vasilenko,Splines: Theory, Algorithms, and Software [in Russian], Nauka, Novosibirsk (1984).

    Google Scholar 

  10. L. L. Schumaker, “Fitting surfaces to scattered data,” in:Approx. Theory. II (Lorentz G. G., Chui C. K., Schumaker L. L., editors) Academic Press, New York (1976), p. 203–268.

    Google Scholar 

  11. C. A. Micchelli and T. J. Rivlin,A Survey of Optimal Recovery. Optimal estimation in approximation theory. Plenum Press, New York (1977).

    Google Scholar 

  12. O. V. Matveev, “Approximative properties ofD m-splines,”Dokl. Akad. Nauk SSSR [Soviet Math. Dokl.],321, No. 1, 14–18 (1991).

    MATH  Google Scholar 

  13. O. V. Matveev, “Some methods for recovering functions of variables ranging over chaotic grids,”Dokl. Akad. Nauk SSSR [Soviet Math. Dokl.],326, No. 4, 605–609 (1992).

    MATH  Google Scholar 

  14. A. A. Zhensykbaev, “Spline approximation and optimal recovery of operators,”Mat. Sb. [Math. USSR-Sb.],184, No. 12, 3–22 (1993).

    MATH  Google Scholar 

  15. A. A. Zhensykbaev, “Optimal recovery of operators and spline approximations,”Dokl. Akad. Nauk Respubliki Kazakhstan, No. 2, 8–13 (1992).

    Google Scholar 

  16. L. Nirenberg,Topics in Nonlinear Functional Analysis, Courant Institute of Mathematical Sciences, New York University, New York (1974).

    Google Scholar 

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Translated fromMatematicheskie Zametki, Vol. 58, No. 4, pp. 512–524, October, 1995.

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Zhensykbaev, A.A. Nonlinear interpolation and norm minimization. Math Notes 58, 1033–1041 (1995). https://doi.org/10.1007/BF02305091

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