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Towards Optimal Compression of Meteorological Data: A Case Study of Using Interval-Motivated Overestimators in Global Optimization

  • Olga Kosheleva
Part of the Optimization and Its Applications book series (SOIA, volume 4)

Abstract

The existing image and data compression techniques try to minimize the mean square deviation between the original data f(x, y, z) and the compressed-decompressed data f(x, y, z). In many practical situations, reconstruction that only guaranteed mean square error over the data set is unacceptable.

Keywords

Mean Square Error Meteorological Data Data Compression JPEG2000 Compression Interval Uncertainty 
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

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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Olga Kosheleva
    • 1
  1. 1.Department of Electrical and Computer Engineering and Department of Teacher EducationUniversity of TexasEl PasoUSA

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