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The Resource Computing statistics under interval and fuzzy uncertainty : applications to computer science and engineering, Hung T. Nguyen...[et al.], (electronic resource)
Computing statistics under interval and fuzzy uncertainty : applications to computer science and engineering, Hung T. Nguyen...[et al.], (electronic resource)
Resource Information
The item Computing statistics under interval and fuzzy uncertainty : applications to computer science and engineering, Hung T. Nguyen...[et al.], (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.This item is available to borrow from all library branches.
Resource Information
The item Computing statistics under interval and fuzzy uncertainty : applications to computer science and engineering, Hung T. Nguyen...[et al.], (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.
This item is available to borrow from all library branches.
 Summary
 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
 Language
 eng
 Extent
 1 online resource (xi, 430 p.)
 Contents

 Part I Computing Statistics under Interval and Fuzzy Uncertainty: Formulation of the Problem and an Overview of General Techniques Which Can Be Used for Solving this Problem
 Part II Algorithms for Computing Statistics Under Interval and Fuzzy Uncertainty
 Part III Towards Computing Statistics under Interval and Fuzzy Uncertainty: Gauging the Quality of the Input Data
 Part IV Applications
 Part V Beyond Interval and Fuzzy Uncertainty
 Isbn
 9783642249044
 Label
 Computing statistics under interval and fuzzy uncertainty : applications to computer science and engineering
 Title
 Computing statistics under interval and fuzzy uncertainty
 Title remainder
 applications to computer science and engineering
 Statement of responsibility
 Hung T. Nguyen...[et al.]
 Subject

 Electronic books
 IngĂ©nierie
 Mathematical statistics  Data processing
 Mathematical statistics  Data processing
 Engineering
 Electronic resources
 Mathematical statistics  Data processing
 Mathematical statistics  Data processing
 Mathematical statistics  Data processing
 Artificial intelligence
 Engineering mathematics
 Mathematical statistics  Data processing
 Language
 eng
 Summary
 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
 Cataloging source
 GW5XE
 Image bit depth
 0
 LC call number
 QA276.4
 LC item number
 .C66 2012
 Literary form
 non fiction
 Nature of contents
 dictionaries
 http://library.link/vocab/relatedWorkOrContributorDate
 1944
 http://library.link/vocab/relatedWorkOrContributorName

 SpringerLink
 Nguyen, Hung T.
 Series statement
 Studies in Computational Intelligence,
 Series volume
 393
 http://library.link/vocab/subjectName

 Mathematical statistics
 Mathematical statistics
 IngĂ©nierie
 Label
 Computing statistics under interval and fuzzy uncertainty : applications to computer science and engineering, Hung T. Nguyen...[et al.], (electronic resource)
 Antecedent source
 mixed
 Bibliography note
 Includes bibliographical references (p. 401424) and index
 Color
 not applicable
 Contents
 Part I Computing Statistics under Interval and Fuzzy Uncertainty: Formulation of the Problem and an Overview of General Techniques Which Can Be Used for Solving this Problem  Part II Algorithms for Computing Statistics Under Interval and Fuzzy Uncertainty  Part III Towards Computing Statistics under Interval and Fuzzy Uncertainty: Gauging the Quality of the Input Data  Part IV Applications  Part V Beyond Interval and Fuzzy Uncertainty
 Dimensions
 unknown
 Extent
 1 online resource (xi, 430 p.)
 File format
 multiple file formats
 Form of item

 online
 electronic
 Isbn
 9783642249044
 Level of compression
 uncompressed
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number

 (OCoLC)765267146
 (OCoLC)ocn765267146
 Label
 Computing statistics under interval and fuzzy uncertainty : applications to computer science and engineering, Hung T. Nguyen...[et al.], (electronic resource)
 Antecedent source
 mixed
 Bibliography note
 Includes bibliographical references (p. 401424) and index
 Color
 not applicable
 Contents
 Part I Computing Statistics under Interval and Fuzzy Uncertainty: Formulation of the Problem and an Overview of General Techniques Which Can Be Used for Solving this Problem  Part II Algorithms for Computing Statistics Under Interval and Fuzzy Uncertainty  Part III Towards Computing Statistics under Interval and Fuzzy Uncertainty: Gauging the Quality of the Input Data  Part IV Applications  Part V Beyond Interval and Fuzzy Uncertainty
 Dimensions
 unknown
 Extent
 1 online resource (xi, 430 p.)
 File format
 multiple file formats
 Form of item

 online
 electronic
 Isbn
 9783642249044
 Level of compression
 uncompressed
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number

 (OCoLC)765267146
 (OCoLC)ocn765267146
Subject
 Artificial intelligence
 Electronic books
 Electronic resources
 Engineering
 Engineering mathematics
 IngĂ©nierie
 Mathematical statistics  Data processing
 Mathematical statistics  Data processing
 Mathematical statistics  Data processing
 Mathematical statistics  Data processing
 Mathematical statistics  Data processing
 Mathematical statistics  Data processing
Genre
Member of
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<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.bu.edu/portal/Computingstatisticsunderintervalandfuzzy/vwlSoxmVuyI/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.bu.edu/portal/Computingstatisticsunderintervalandfuzzy/vwlSoxmVuyI/">Computing statistics under interval and fuzzy uncertainty : applications to computer science and engineering, Hung T. Nguyen...[et al.], (electronic resource)</a></span>  <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.bu.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.bu.edu/">Boston University Libraries</a></span></span></span></span></div>