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Applied Interval Analysis

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The article was published on 2001-08-30 and is currently open access. It has received 1709 citations till now. The article focuses on the topics: Interval arithmetic.

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Citations
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Book

Introduction to Interval Computation

TL;DR: In this paper, the authors present an ALGOLGOL-based approach for the inclusion of complex Zeros of polynomials of a function of one real variable in a system of linear systems of equations.
Journal ArticleDOI

Survey of sampling-based methods for uncertainty and sensitivity analysis

TL;DR: Sampling-based methods for uncertainty and sensitivity analysis are reviewed and special attention is given to the determination of sensitivity analysis results.
Book

Digital arithmetic

TL;DR: Digital Arithmetic, two of the field's leading experts, deliver a unified treatment of digital arithmetic, tying underlying theory to design practice in a technology-independent manner, to develop sound solutions, avoid known mistakes, and repeat successful design decisions.
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On Identifiability of Nonlinear ODE Models and Applications in Viral Dynamics

TL;DR: This article reviews identifiability analysis methodologies for nonlinear ODE models developed in the past one to two decades, including structural identifiable analysis, practical identIFiability analysis and sensitivity-based identifability analysis.
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Complete search in continuous global optimization and constraint satisfaction

TL;DR: This survey covers the state of the art of techniques for solving general-purpose constrained global optimization problems and continuous constraint satisfaction problems, with emphasis on complete techniques that provably find all solutions (if there are finitely many).
References
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Journal ArticleDOI

Parameter-Bounding Algorithms for Linear Errors in Variables Models

TL;DR: The static and dynamic cases of parameter bounding for errors-in-variables models are discussed and their differences clarified, and algorithms to calculate parameter bounds for such models are presented.
Book ChapterDOI

Applications of Software for Automatic Differentiation in Numerical Computation

TL;DR: This paper describes construction and applications of Software for automatic differentiation and examples from actual experience are cited to illustrate the theory.
Proceedings ArticleDOI

A combined interval and floating point multiplier

TL;DR: The design of a multiplier that performs either interval or floating point multiplication is presented, which requires only slightly more area and delay than a conventional floating point multiplier, and is one to two orders of magnitude faster than software implementations of interval multiplication.