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Global Optimization and Constraint Satisfaction

Overview of attention for book
Cover of 'Global Optimization and Constraint Satisfaction'

Table of Contents

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    Book Overview
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    Chapter 1 Efficient Pruning Technique Based on Linear Relaxations
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    Chapter 2 Inter-block Backtracking: Exploiting the Structure in Continuous CSPs
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    Chapter 3 Accelerating Consistency Techniques and Prony’s Method for Reliable Parameter Estimation of Exponential Sums
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    Chapter 4 Convex Programming Methods for Global Optimization
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    Chapter 5 A Method for Global Optimization of Large Systems of Quadratic Constraints
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    Chapter 6 A Comparison of Methods for the Computation of Affine Lower Bound Functions for Polynomials
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    Chapter 7 Using a Cooperative Solving Approach to Global Optimization Problems
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    Chapter 8 Global Optimization of Convex Multiplicative Programs by Duality Theory
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    Chapter 9 High-Fidelity Models in Global Optimization
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    Chapter 10 Incremental Construction of the Robot’s Environmental Map Using Interval Analysis
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    Chapter 11 Nonlinear Predictive Control Using Constraints Satisfaction
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    Chapter 12 Gas Turbine Model-Based Robust Fault Detection Using a Forward – Backward Test
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    Chapter 13 Benchmarking on Approaches to Interval Observation Applied to Robust Fault Detection
Attention for Chapter 4: Convex Programming Methods for Global Optimization
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Citations

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Chapter title
Convex Programming Methods for Global Optimization
Chapter number 4
Book title
Global Optimization and Constraint Satisfaction
Published by
Springer, Berlin, Heidelberg, November 2003
DOI 10.1007/11425076_4
Book ISBNs
978-3-54-026003-5, 978-3-54-032041-8
Authors

J. N. Hooker, Hooker, J. N.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 33%
Unknown 2 67%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 67%
Professor 1 33%
Professor > Associate Professor 1 33%
Readers by discipline Count As %
Computer Science 2 67%
Engineering 1 33%

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