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Learn to characterize the effect of uncertainty on numerical models in real-world applications

Table of Contents

1. ELEMENTS OF PROBABILITY THEORY AND STOCHASTIC PROCESSES 2. MAXIMUM ENTROPY AND INFORMATION 3. REPRESENTATION OF RANDOM VARIABLES 4. LINEAR ALGEBRAIC EQUATIONS UNDER UNCERTAINTY 5. NONLINEAR ALGEBRAIC EQUATIONS INVOLVING RANDOM PARAMETERS 6. DIFFERENTIAL EQUATIONS UNDER UNCERTAINTY 7. OPTIMIZATION UNDER UNCERTAINTY 8. RELIABILITY-BASED OPTIMIZATION

About the Author

Eduardo Souza De Cursi is Professor at the National Institute for Applied Sciences in Rouen, France, where he is also Dean of International Affairs and Director of the Laboratory for the Optimization and Reliability in Structural Mechanics.

Reviews

"...a deepening to the mathematics of uncertainty quantification and stochastic modeling through the tools of functional analysis...the perspective on UQ that runs through this book is firmly grounded in probability theory and Hilbert spaces; the elements of linear functional analysis and measure/probability theory are provided." --Zentralblatt MATH

"...an excellent introduction for newcomers and a practical reference for established practitioners…Practical techniques are illustrated by well-chosen and thoroughly worked-out examples." --MAA Reviews