Stochastic Systems : Uncertainty Quantification and Propagation
Uncertainty is an inherent feature of both properties of physical systems and the inputs to these systems that needs to be quantified for cost effective and reliable designs. The states of these systems satisfy equations with random entries, referred to as stochastic equations, so that they are rand...
保存先:
| 第一著者: | |
|---|---|
| フォーマット: | Livre numérique |
| 言語: | Anglais |
| 出版事項: |
London :
Springer London
[20..].
Cham : Springer Nature |
| 版: | 1st ed. 2012. |
| シリーズ: | Springer Series in Reliability Engineering
|
| オンライン･アクセス: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| 注記: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Stochastic systems, uncertainty, quantification, and propagation, Mircea Grigoriu, 2012, London, Springer, 1 vol. (XI-529 p.), Springer series in reliability engineering, 978-1-4471-2326-2 • Stochastic systems, uncertainty, quantification, and propagation, Mircea Grigoriu, 2012, London, Springer, 1 vol. (XI-529 p.), Springer series in reliability engineering, 978-1-4471-2326-2 • Stochastic Systems, Texte imprimé, 9781447123286 • Stochastic Systems, Texte imprimé, 9781447159483 |
目次:
- Probability Essentials Random Functions Probabilistic Models Stochastic Integrals and Itô's Formula Properties of Solutions of Stochastic Equations Stochastic Equations with Small Uncertainty Stochastic Algebraic Equations Stochastic Differential Equations with Deterministic Coefficients Stochastic Differential Equations with Random Coefficients