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Variable Metric Methods and Filtering Theory

  • Sanjoy K. Mitter
  • Pal Toldalagi
Conference paper
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 162)

Abstract

In this paper we show that there is a close relationship between variable metric methods of function minimization and filtering of linear stochastic systems with disturbances which are modelled as unknown but bounded functions. We develop new variable metric algorithms for function minimization.

Keywords

Support Function Function Minimization Rapid Convergence Filter Theory Derivative Computation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    D. Bertsekas, “Control of Uncertain Systems with a Set Membership Description of Uncertainty,” Ph.D. Thesis, Department of Electrical Engineering, M.I.T., 1971.Google Scholar
  2. [2]
    S. K. Mitter and P. Toldalagi, to appear.Google Scholar
  3. [3]
    M.J.D. Powell, “Convergence Properties of a Class of Minimization Algorithms, in Nonlinear Programming, Vol. 2, editors Mangasarian, Meyer and Robinson, McGraw-Hill, New York, 1975.Google Scholar
  4. [4]
    S. W. Thomas, “Sequential Estimation Techniques for Quasi-Newton Algorithms, Cornell University, Department of Computer Science, Technical Report TR75-227, 1975.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1978

Authors and Affiliations

  • Sanjoy K. Mitter
    • 1
  • Pal Toldalagi
    • 1
  1. 1.Department of Electrical Engineering and Computer ScienceMassachusetts Institute of TechnologyCambridgeUSA

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