Uncertainty quantification and stochastic modeling with Matlab
β Scribed by Sampaio, Rubens;Souza de Cursi, J. E
- Publisher
- ISTE Press
- Year
- 2015
- Tongue
- English
- Leaves
- 457
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
- 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
β¦ Subjects
Stochastic models;Uncertainty (Information theory)
π SIMILAR VOLUMES
<p>Uncertainty Quantification (UQ) is a relatively new research area which describes the methods and approaches used to supply quantitative descriptions of the effects of uncertainty, variability and errors in simulation problems and models. It is rapidly becoming a field of increasing importance, w
<span><p>This book presents techniques for determining uncertainties in numerical solutions with applications in the fields of business administration, civil engineering, and economics, using Excel as a computational tool. Also included are solutions to uncertainty problems involving stochastic meth
<p><span>This book presents techniques for determining uncertainties in numerical solutions with applications in the fields of business administration, civil engineering, and economics, using Excel as a computational tool. Also included are solutions to uncertainty problems involving stochastic meth
<p><span>This book presents techniques for determining uncertainties in numerical solutions with applications in the fields of business administration, civil engineering, and economics, using Excel as a computational tool. Also included are solutions to uncertainty problems involving stochastic meth
Introduction -- Essentials of Probability Theory -- Random Functions -- Stochastic Integrals -- ItoΜ's Formula and Applications -- Probabilistic Models -- Stochastic Ordinary Differential and Difference Equations -- Stochastic Algebraic Equations -- Stochastic Partial Differential Equations