Implicit Filtering and Optimal Design Problems

  • P. Gilmore
  • C. T. Kelley
  • C. T. Miller
  • G. A. Williams
Part of the Progress in Systems and Control Theory book series (PSCT, volume 19)


Implicit filtering is a form of the gradient projection method of Bertsekas in which the stepsize in a difference approximation of the gradient is changed as the iteration progresses. In this way the algorithm is able to avoid certain types of local minima and in some cases find accurate approximations to the global minimum. The algorithm is particularly effective in avoiding local minima that are caused by high-frequency low-amplitude terms in the objective function. In this report we will discuss the algorithm and its theoretical properties. We will also present applications for modeling of subsurface contaminant transport and high-field magnet design.


Line Search Merit Function Pulse Magnet Nonlinear Constraint Gradient Projection Method 
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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Copyright information

© Springer Science+Business Media New York 1995

Authors and Affiliations

  • P. Gilmore
    • 1
  • C. T. Kelley
    • 2
  • C. T. Miller
    • 3
  • G. A. Williams
    • 3
  1. 1.National High Magnetic Field LaboratoryFlorida State UniversityTallahasseeUSA
  2. 2.Center for Research in Scientific Computation and Department of MathematicsNorth Carolina State UniversityRaleighUSA
  3. 3.Department of Environmental Sciences and EngineeringUniversity of North CarolinaChapel HillUSA

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