Computing Statistics Under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering - Couverture rigide

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

Couverture rigide

ISBN 10 : 3642249043 ISBN 13 : 9783642249044

Editeur : Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 2011

Synopsis

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.

Détails de l'édition

• Éditeur: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
• Date d'édition: 2011
• Langue: anglais
• ISBN 10: 3642249043
• ISBN 13: 9783642249044
• Reliure: Relié
• Nombre de pages: 432
• Coordonnées du fabricant: non disponible
• Personne responsable: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Allemagne