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

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

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

Download Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (Studies in Computational Intelligence) eBook
ISBN:
3642249043
Author:
Hung T. Nguyen,Vladik Kreinovich,Berlin Wu,Gang Xiang
Category:
Computer Science
Language:
English
Publisher:
Springer; 2012 edition (November 2, 2011)
Pages:
432 pages
EPUB book:
1869 kb
FB2 book:
1120 kb
DJVU:
1162 kb
Other formats
docx doc lrf mbr
Rating:
4.7
Votes:
471


This book shows how to compute statistics under such interval and fuzzy uncertainty.

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. The main goal is to present algorithms for computation of statistical characteristics (like variance) but under interval and fuzzy.

Электронная книга "Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering", Hung T. Nguyen, Vladik Kreinovich, Berlin Wu, Gang Xiang

Электронная книга "Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering", Hung T. Nguyen, Vladik Kreinovich, Berlin Wu, Gang Xiang. Эту книгу можно прочитать в Google Play Книгах на компьютере, а также на устройствах Android и iOS. Выделяйте текст, добавляйте закладки и делайте заметки, скачав книгу "Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering" для чтения в офлайн-режиме.

Hung T. Скачать (pdf, . 0 Mb).

under Interval and Fuzzy Uncertainty : Applications to Computer Science and . In many practical situations, we are interested in statistics characterizing a population of objects: .

book by Hung T. Nguyêñ. Computing Statistics under Interval and Fuzzy Uncertainty : Applications to Computer Science and Engineering. 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.

from book Computing statistics under interval and fuzzy uncertainty. Studies in Computational Intelligence

from book Computing statistics under interval and fuzzy uncertainty. Applications to computer science and engineering (p. 61-264). Studies in Computational Intelligence. Chapter · January 2012 with 15 Reads. How we measure 'reads'.

6 Abstract In many engineering applications, we have to combine probabilistic and interval uncertainty.

1 FAST ALGORITHMS FOR COMPUTING STATISTICS UNDER INTERVAL UNCERTAINTY, WITH APPLICATIONS TO COMPUTER SCIENCE AND TO ELECTRICAL AND COMPUTER ENGINEERING GANG XIANG Department of Computer Science APPROVED: Vladik Kreinovich, Chair, P. Martine Ceberio, P. Scott A. Starks, P. Dean of the Graduate School. 6 Abstract In many engineering applications, we have to combine probabilistic and interval uncertainty.

We aim to show you accurate product information. Manufacturers, suppliers and others provide what you see here, and we have not verified it. See our disclaimer. Computing Statistics Under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering (2012). Policies & Plans. See any care plans, options and policies that may be associated with this product. Electrode, App-product, e, DC-scus-prod-a2, ENV-prod-a, PROF-PROD, VER-29.

Поиск книг BookFi BookSee - Download books for free. Computing Statistics under Interval and Fuzzy Uncertainty: Applications to Computer Science and Engineering. Hung T. Cem Kaner, Jack Falk, Hung Q. Nguyen.

Computing Statistics under Interval and Fuzzy Uncertainty, by Hung T. Nguyen, Vladik Kreinovich, Berlin . Perceptual Computing: Aiding People in Making Subjective Judgments, by Jerry M. Mendel and Dongrui Wu, IEEE Press and Wiley, 2010, ISBN 978-0-470-47876-9. Nguyen, Vladik Kreinovich, Berlin Wu, and Gang Xiang, Springer Verlag, Berlin, Heidelberg, 2012, ISBN 978-3-642-24904-4. Validated Numerics: A Short Introduction to Rigorous Computations, by Warwick Tucker, Princeton University Press, 2011, ISBN 978-0691147819.

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.