Smoothing and interpolation in a convex subset of a Hilbert space : II. The semi-norm case

Charles A. Micchelli; Florencio I. Utreras

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique (1991)

  • Volume: 25, Issue: 4, page 425-440
  • ISSN: 0764-583X

How to cite

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Micchelli, Charles A., and Utreras, Florencio I.. "Smoothing and interpolation in a convex subset of a Hilbert space : II. The semi-norm case." ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique 25.4 (1991): 425-440. <http://eudml.org/doc/193634>.

@article{Micchelli1991,
author = {Micchelli, Charles A., Utreras, Florencio I.},
journal = {ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique},
keywords = {convex constraints; interpolation; smoothing; Hilbert space; constrained best interpolation; bounded linear operator; finite dimensional kernel; orthogonal projection; min-max problem; reduction of computational cost; decomposition; smooth monotone interpolation; least norm solution},
language = {eng},
number = {4},
pages = {425-440},
publisher = {Dunod},
title = {Smoothing and interpolation in a convex subset of a Hilbert space : II. The semi-norm case},
url = {http://eudml.org/doc/193634},
volume = {25},
year = {1991},
}

TY - JOUR
AU - Micchelli, Charles A.
AU - Utreras, Florencio I.
TI - Smoothing and interpolation in a convex subset of a Hilbert space : II. The semi-norm case
JO - ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique
PY - 1991
PB - Dunod
VL - 25
IS - 4
SP - 425
EP - 440
LA - eng
KW - convex constraints; interpolation; smoothing; Hilbert space; constrained best interpolation; bounded linear operator; finite dimensional kernel; orthogonal projection; min-max problem; reduction of computational cost; decomposition; smooth monotone interpolation; least norm solution
UR - http://eudml.org/doc/193634
ER -

References

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  1. [1] L. D. IRVINE, S. P. MARIN and P. W. SMITH, Constrained interpolation and smoothing, Constr Approx, 2 (1986), 129-152. Zbl0596.41012MR891965
  2. [2] P. J. LAURENT, Approximation et Optimization, Herman, Paris, 1972. 
  3. [3] C. A. MICCHELLI, P. W. SMITH, J. SWETITS and J. D. WARD, Constrained LP approximation, Constr Approx, 1 (1985), 93-102. Zbl0582.41002MR766097
  4. [4] C. A. MICCHELLI and F. UTRERAS, Smoothing and interpolation in a convex subset of a Hilbert space, SIAM J. Sci. Statist. Comput, 9 (1988), 728-746. Zbl0651.65046MR945935
  5. [5] R. T. ROCKAFELLAR, Convex Analysis, Princeton University Press, Princeton, N. J., 1970. Zbl0193.18401MR274683
  6. [6] F. UTRERAS, Smoothing noisy data under monotonicity constraints existence, characterization and convergence, rates Numer. Math., 74 (1985), 611-625 Zbl0606.65006MR812623
  7. [7] F. J. BEUTLER and W. L. ROOT, The operator pseudoinverse in control and systems identification, in Generalized Inverses and Applications, eds Z. Nashed, Academie Press, New York, 1973. Zbl0367.93001MR490311
  8. [8] C. K. CHUI, F. DEUTSCH and J. D. WARD, Constrained best approximation in Hilbert space, Constr. Approx., 6 (1990), 35-64. Zbl0682.41034MR1027508
  9. [9] N. DYN and W. H. WONG, On the characterization of non-negative volume matching surface splines, J. Approx. Theory, 31 (1987), 1-10. Zbl0645.41010MR906755

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