Read Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence, 393)

Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence, 393)

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Description: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.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence, 393). To get started finding Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence, 393), you are right to find our website which has a comprehensive collection of manuals listed.
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ISBN: 3642249043

Description: 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.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence, 393). To get started finding Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence, 393), you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence, 393)

Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence, 393)

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