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Uncertainty Modeling for Engineering Applications

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Cover of 'Uncertainty Modeling for Engineering Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Quadrature Strategies for Constructing Polynomial Approximations
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    Chapter 2 Weighted Reduced Order Methods for Parametrized Partial Differential Equations with Random Inputs
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    Chapter 3 A New Approach for State Estimation
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    Chapter 4 Data-Efficient Sensitivity Analysis with Surrogate Modeling
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    Chapter 5 Surrogate Modeling for Fast Experimental Assessment of Specific Absorption Rate
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    Chapter 6 Stochastic Dosimetry for Radio-Frequency Exposure Assessment in Realistic Scenarios
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    Chapter 7 Application of Polynomial Chaos Expansions for Uncertainty Estimation in Angle-of-Arrival Based Localization
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    Chapter 8 Reducing the Statistical Complexity of EMC Testing: Improvements for Radiated Experiments Using Stochastic Collocation and Bootstrap Methods
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    Chapter 9 On the Various Applications of Stochastic Collocation in Computational Electromagnetics
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    Chapter 10 Hybrid Possibilistic-Probabilistic Approach to Uncertainty Quantification in Electromagnetic Compatibility Models
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    Chapter 11 Measurement Uncertainty Cannot Always Be Calculated
Attention for Chapter 8: Reducing the Statistical Complexity of EMC Testing: Improvements for Radiated Experiments Using Stochastic Collocation and Bootstrap Methods
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