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Probabilistic and Randomized Methods for Design under Uncertainty

In many engineering design and optimization problems, the presence of uncertainty in the data is a central and critical issue. Different fields of engineering use different ways to describe this uncertainty and adopt a variety of techniques to devise designs that are at least partly insensitive or r...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Calafiore, Giuseppe (Editor ), Dabbene, Fabrizio (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Springer London : Imprint: Springer, 2006.
Edición:1st ed. 2006.
Temas:
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Chance-Constrained and Stochastic Optimization
  • Scenario Approximations of Chance Constraints
  • Optimization Models with Probabilistic Constraints
  • Theoretical Framework for Comparing Several Stochastic Optimization Approaches
  • Optimization of Risk Measures
  • Robust Optimization and Random Sampling
  • Sampled Convex Programs and Probabilistically Robust Design
  • Tetris: A Study of Randomized Constraint Sampling
  • Near Optimal Solutions to Least-Squares Problems with Stochastic Uncertainty
  • The Randomized Ellipsoid Algorithm for Constrained Robust Least Squares Problems
  • Randomized Algorithms for Semi-Infinite Programming Problems
  • Probabilistic Methods in Identification and Control
  • A Learning Theory Approach to System Identification and Stochastic Adaptive Control
  • Probabilistic Design of a Robust Controller Using a Parameter-Dependent Lyapunov Function
  • Probabilistic Robust Controller Design: Probable Near Minimax Value and Randomized Algorithms
  • Sampling Random Transfer Functions
  • Nonlinear Systems Stability via Random and Quasi-Random Methods
  • Probabilistic Control of Nonlinear Uncertain Systems
  • Fast Randomized Algorithms for Probabilistic Robustness Analysis.