Adaptive Methods

  • O. P. Le MaîtreEmail author
  • O. M. Knio
Part of the Scientific Computation book series (SCIENTCOMP)


Adaptive schemes generally aim at reducing CPU cost by adjusting the quality of the representation to capture essential features of the solution. In this chapter, we explore four different strategies for performing such refinement. The following developments are motivated in part by the experiences with MW representations outlined in the previous chapter. In particular, these indicated that while “refinement” can be naturally implemented in conjunction with wavelet representation, for instance by increasing the levels of details, a uniform or brute-force refinement is likely to require excessive CPU resources, even for simple examples. Adaptive schemes consequently strive to perform such refinements locally where needed, in an effort to minimize necessary computational resources.


Dual Problem Posteriori Error Burger Equation Adaptive Method Approximation Space 
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 B.V. 2010

Authors and Affiliations

  1. 1.LIMSI-CNRSUniversité Paris-Sud XIOrsay cedexFrance
  2. 2.Department of Mechanical EngineeringThe Johns Hopkins UniversityBaltimoreUSA

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