Skip to main content
Log in

Quasi interiors, lagrange multipliers, andL p spectral estimation with lattice bounds

  • Contributed Papers
  • Published:
Journal of Optimization Theory and Applications Aims and scope Submit manuscript

Abstract

Lagrange multipliers useful in characterizations of solutions to spectral estimation problems are proved to exist in the absence of Slater's condition provided a new constraint involving the quasi-relative interior holds. We also discuss the quasi interior and its relation to other generalizations of the interior of a convex set and relationships between various constraint qualifications. Finally, we characterize solutions to theL p spectral estimation problem with the added constraint that the feasible vectors lie in a measurable strip [α, β].

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Goodrich, R. K., andSteinhardt, A. O.,L 2 Spectral Estimation, SIAM Journal on Applied Mathematics, Vol. 46, pp. 417–426, 1986.

    Google Scholar 

  2. Goodrich, R. K., Steinhardt, A. O., andRoberts, R. A.,Spectral Estimation via Minimum Energy Correlation Extension, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 33, pp. 1509–1515, 1985.

    Google Scholar 

  3. Cole, R., andGoodrich, R. K.,L p Spectral Analysis with an L Upper Bound, Journal of Optimization Theory and Applications, Vol. 72, No. 2, pp. 321–355, 1993.

    Google Scholar 

  4. Borwein, J. M., andLewis, A. S.,Partially Finite Convex Programming, Parts 1 and 2, Mathematical Programming, Vol. 57, pp. 15–48, 1992 and Vol. 57, pp. 49–83, 1992.

    Google Scholar 

  5. Cole, R.,L p Spectral Analysis with an L Upper Bound, PhD Thesis, University of Colorado, Boulder, Colorado, 1990.

    Google Scholar 

  6. Klee, V. L.,Convex Sets in Linear Spaces, Duke Mathematics Journal, Vol. 16, pp. 443–466, 1948.

    Google Scholar 

  7. Klee, V. L.,Extremal Structure of Convex Sets, Mathematische Zeitschrift, Vol. 69, pp. 90–104, 1958.

    Google Scholar 

  8. Peressini, A. L.,Ordered Topological Vector Spaces, Harper, New York, New York, 1967.

    Google Scholar 

  9. Gowda, M. S., andTeboulle, M.,A Comparison of Constraint Qualifications in Infinite-Dimensional Convex Programming, SIAM Journal on Control and Optimization, Vol. 28, pp. 925–935, 1990.

    Google Scholar 

  10. Fullerton, R. E., andBraunschweiger, C. C.,Quasi-Interior Points and the Extension of Linear Functionals, Mathematics Annalen, Vol. 162, pp. 214–224, 1966.

    Google Scholar 

  11. Fullerton, R. E., andBraunschweiger, C. C.,Quasi-Interior Points of Cones, Technical Report 2, University of Delaware, Newark, Delaware, 1963.

    Google Scholar 

  12. Schaefer, H. H.,Banach Lattices and Positive Operators, Springer-Verlag, New York, New York, 1974.

    Google Scholar 

  13. Bazarra, M. S., andShetty, C. M.,Foundations of Optimization. Springer-Verlag, New York, New York, 1976.

    Google Scholar 

  14. Slater, M.,Lagrange Multipliers Revisited: A Contribution to Nonlinear Programming, Discussion Paper 403, Cowles Commission, 1950.

  15. Borwein, J. M., andWolkowicz, H.,A Simple Constraint Qualification in Infinite-Dimensional Programming, Mathematical Programming, Vol. 35, pp. 83–96, 1986.

    Google Scholar 

  16. Micchelli, C. A., andUtreras, F. I.,Smoothing and Interpolation in a Convex Subset of a Hilbert Space, SIAM Journal on Scientific and Statistical Computation, Vol. 9, pp. 728–746, 1988.

    Google Scholar 

  17. Irvine, L. D., andSmith, P. W.,Constrained Minimization in a Dual Space, International Series of Numerical Mathematics, Birkhäuser Verlag, Basel, Switzerland, Vol. 76, pp. 205–219, 1986.

    Google Scholar 

  18. Luenberger, D. G.,Optimization by Vector Space Methods, John Wiley and Sons, New York, New York, 1969.

    Google Scholar 

  19. Rockafellar, R. T.,Convex Analysis, Princeton University Press, Princeton, New Jersey, 1970.

    Google Scholar 

  20. Holmes, R. B.,Geometric Functional Analysis and Its Applications, Springer-Verlag, New York, New York, 1975.

    Google Scholar 

  21. Rockafellar, R. T.,Conjugate Duality and Optimization, Society for Industrial and Applied Mathematics, Philadelphia, Pennsylvania, 1974.

    Google Scholar 

  22. Limber, M. A.,Quasi Interiors of Convex Sets and Applications to Optimization, PhD Thesis, University of Colorado, Boulder, Colorado, 1991.

    Google Scholar 

  23. Dontchev, A. L.,Duality Methods for Constrained Best Interpolation, Mathematica Balkanica, Vol. 1, pp. 96–105, 1987.

    Google Scholar 

  24. Borwein, J. M., Lewis, A. S., andLimber, M. A.,Entropy Minimization with Lattice Bounds (to appear).

  25. Borwein, J. M., andLimber, M. A.,A Comparison of Entropies in the Underdetermined Moment Problem (to appear).

  26. Borwein, J. M., andLimber, M. A.,On Entropy Maximization via Convex Programming, IEEE Transactions on Signal Processing (to appear).

Download references

Author information

Authors and Affiliations

Authors

Additional information

Communicated by D. G. Luenberger

The authors wish to thank Jonathan M. Borwein and Adrian S. Lewis for many enlightening discussions and useful suggestions. The duality approach to the general problem inL p was suggested by J. M. Borwein.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Limber, M.A., Goodrich, R.K. Quasi interiors, lagrange multipliers, andL p spectral estimation with lattice bounds. J Optim Theory Appl 78, 143–161 (1993). https://doi.org/10.1007/BF00940705

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00940705

Key Words

Navigation