Interval arithmetic

Results: 138



#Item
81PARALLEL SPATIAL ENUMERATION OF IMPLICIT SURFACES USING INTERVAL ARITHMETIC FOR OCTREE GENERATION AND ITS DIRECT VISUALIZATION Nilo Stoltey and Arie Kaufmanz [removed] y School of Computer Science & Elet

PARALLEL SPATIAL ENUMERATION OF IMPLICIT SURFACES USING INTERVAL ARITHMETIC FOR OCTREE GENERATION AND ITS DIRECT VISUALIZATION Nilo Stoltey and Arie Kaufmanz [removed] y School of Computer Science & Elet

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Source URL: fab.cba.mit.edu

Language: English - Date: 2012-04-27 04:55:37
82COMP2610[removed]Information Theory Lecture 16: Arithmetic Coding (cont.) NU Logo UseMarkGuidelines Reid and Aditya Menon

COMP2610[removed]Information Theory Lecture 16: Arithmetic Coding (cont.) NU Logo UseMarkGuidelines Reid and Aditya Menon

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Source URL: mark.reid.name

Language: English - Date: 2015-03-10 00:10:59
83Novel Approaches to Numerical Software with Result Verification  Laurent Granvilliers , Vladik Kreinovich , and Norbert Müller

Novel Approaches to Numerical Software with Result Verification  Laurent Granvilliers , Vladik Kreinovich , and Norbert Müller

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Source URL: www.cs.utep.edu

Language: English - Date: 2003-10-13 19:19:43
84GeoTools Version 3.1 Feature Summary Product Description GeoTools, an MDL application, is a collection of productivity tools developed specifically for

GeoTools Version 3.1 Feature Summary Product Description GeoTools, an MDL application, is a collection of productivity tools developed specifically for

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Source URL: www.ozdata.com.au

Language: English - Date: 2006-09-04 00:40:37
85Towards Joint Use of Probabilities and Intervals in Scientific Computing: What is the Best Transition from Linear to Quadratic Approximation? Martine Ceberio1 , Vladik Kreinovich1 , and Lev Ginzburg2,3 1

Towards Joint Use of Probabilities and Intervals in Scientific Computing: What is the Best Transition from Linear to Quadratic Approximation? Martine Ceberio1 , Vladik Kreinovich1 , and Lev Ginzburg2,3 1

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Source URL: www.cs.utep.edu

Language: English - Date: 2004-03-09 18:28:45
86Comments and Suggestions for the Proposed Standard Interval Library for C++ Workshop on New Perspectives in Enclosure Methods J. Wolff v. Gudenberg Dagstuhl Oct 2005 The participants of the workshop - including some of t

Comments and Suggestions for the Proposed Standard Interval Library for C++ Workshop on New Perspectives in Enclosure Methods J. Wolff v. Gudenberg Dagstuhl Oct 2005 The participants of the workshop - including some of t

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Source URL: www.cs.utep.edu

Language: English - Date: 2005-10-19 17:20:19
87Exact Bounds on Finite Populations of Interval Data Scott Ferson1 , Lev Ginzburg1 , Vladik Kreinovich2 , Luc Longpr´e, and Monica Aviles2 1

Exact Bounds on Finite Populations of Interval Data Scott Ferson1 , Lev Ginzburg1 , Vladik Kreinovich2 , Luc Longpr´e, and Monica Aviles2 1

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Source URL: www.cs.utep.edu

Language: English - Date: 2004-09-23 18:04:54
88Conquering Numerical Error David H. Bailey http://www.davidhbailey.com Computational Research Dept., Lawrence Berkeley National Laboratory Computer Science Department, University of California, Davis

Conquering Numerical Error David H. Bailey http://www.davidhbailey.com Computational Research Dept., Lawrence Berkeley National Laboratory Computer Science Department, University of California, Davis

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Source URL: mathsofplanetearth.org.au

Language: English - Date: 2013-07-16 22:16:40
89Interval-Valued and Fuzzy-Valued Random Variables: From Computing Sample Variances to Computing Sample Covariances Jan B. Beck1 , Vladik Kreinovich1 , and Berlin Wu2 1 2

Interval-Valued and Fuzzy-Valued Random Variables: From Computing Sample Variances to Computing Sample Covariances Jan B. Beck1 , Vladik Kreinovich1 , and Berlin Wu2 1 2

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Source URL: www.cs.utep.edu

Language: English - Date: 2004-04-18 13:14:58
90Information Theory, Pattern Recognition and Neural Networks Handout 2 February 5, [removed]Course summary: central chapters Data compression and noisy channel coding (Chapters 1–6, 8–10, 14). (But omitting section 6.4

Information Theory, Pattern Recognition and Neural Networks Handout 2 February 5, [removed]Course summary: central chapters Data compression and noisy channel coding (Chapters 1–6, 8–10, 14). (But omitting section 6.4

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Source URL: www.inference.phy.cam.ac.uk

Language: English - Date: 2008-02-13 08:28:01