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Computing Statistics Under Interval and Fuzzy Uncertainty: Applications to
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Computing Statistics Under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering Hardback - 2011 - 2012th Edition

by Hung T. Nguyen; Vladik Kreinovich; Berlin Wu

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Reader reviews for Computing Statistics Under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering

From the publisher

In many practical situations, we are interested in statistics characterizing a population of objects: e.g. in the mean height of people from a certain area.

Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know the upper bound on this inaccuracy. In this case, we have interval uncertainty: e.g. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 ] 0.1 = 1.1. In other cases, the values are expert estimates, and we only have fuzzy information about the estimation inaccuracy.

This book shows how to compute statistics under such interval and fuzzy uncertainty. The resulting methods are applied to computer science (optimal scheduling of different processors), to information technology (maintaining privacy), to computer engineering (design of computer chips), and to data processing in geosciences, radar imaging, and structural mechanics.

From the rear cover

In many practical situations, we are interested in statistics characterizing a population of objects: e.g. in the mean height of people from a certain area.

Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know the upper bound on this inaccuracy. In this case, we have interval uncertainty: e.g. if the measured value is 1.0, and inaccuracy is bounded by 0.1, then the actual (unknown) value of the quantity can be anywhere between 1.0 - 0.1 = 0.9 and 1.0 + 0.1 = 1.1. In other cases, the values are expert estimates, and we only have fuzzy information about the estimation inaccuracy.

This book shows how to compute statistics under such interval and fuzzy uncertainty. The resulting methods are applied to computer science (optimal scheduling of different processors), to information technology (maintaining privacy), to computer engineering (design of computer chips), and to data processing in geosciences, radar imaging, and structural mechanics.

Details

  • Title Computing Statistics Under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering
  • Author Hung T. Nguyen; Vladik Kreinovich; Berlin Wu
  • Binding Hardback
  • Edition number 2012th
  • Edition 2012
  • Pages 432
  • Volumes 1
  • Language ENG
  • Publisher Springer
  • Publication date 2011-11-03
  • ISBN 9783642249044 / 3642249043
  • Weight 1.75 lbs (0.79 kg)
  • Dimensions 9.21 x 6.14 x 1 in (23.39 x 15.60 x 2.54 cm)
  • Category Mathematics
  • Dewey Decimal Code 006.3

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Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and...
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Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence)

by Hung T. Nguyen, Vladik Kreinovich, Berlin Wu, Gang Xiang

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Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and...
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Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence)

by Hung T. Nguyen, Vladik Kreinovich, Berlin Wu, Gang Xiang

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Computing Statistics under Interval and Fuzzy Uncertainty : Applications to Computer Science and...

Computing Statistics under Interval and Fuzzy Uncertainty : Applications to Computer Science and Engineering

by Hung T. Nguyen

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9783642249044 / 3642249043
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