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This volume is dedicated to the fundamentals of convex functional analysis. It presents those aspects of functional analysis that are extensively used in various applications to mechanics and control theory. The purpose of the text is essentially two-fold. On the one hand, a bare minimum of the theory required to understand the principles of functional, convex and set-valued analysis is presented. Numerous examples and diagrams provide as intuitive an explanation of the principles as possible. On the other hand, the volume is largely self-contained. Those with a background in graduate mathematics will find a concise summary of all main definitions and theorems. Contents: Classical Abstract Spaces in Functional Analysis Linear Functionals and Linear Operators Common Function Spaces in Applications Differential Calculus in Normed Vector Spaces Minimization of Functionals Convex Functionals Lower Semicontinuous Functionals

Engineering sciences. Technology --- systeemtheorie --- systeembeheer

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Robust design—that is, managing design uncertainties such as model uncertainty or parametric uncertainty—is the often unpleasant issue crucial in much multidisciplinary optimal design work. Recently, there has been enormous practical interest in strategies for applying optimization tools to the development of robust solutions and designs in several areas, including aerodynamics, the integration of sensing (e.g., laser radars, vision-based systems, and millimeter-wave radars) and control, cooperative control with poorly modeled uncertainty, cascading failures in military and civilian applications, multi-mode seekers/sensor fusion, and data association problems and tracking systems. The contributions to this book explore these different strategies. The expression "optimization-directed” in this book’s title is meant to suggest that the focus is not agonizing over whether optimization strategies identify a true global optimum, but rather whether these strategies make significant design improvements. Audience .

System theory. --- Mathematical optimization. --- Programming (Mathematics) --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Systems, Theory of --- Systems science --- Science --- Philosophy --- Mathematical programming --- Goal programming --- Algorithms --- Functional equations --- Mathematical optimization --- Mathematics. --- Systems theory. --- Optimization. --- Applications of Mathematics. --- Systems Theory, Control. --- Math --- Applied mathematics. --- Engineering mathematics. --- Engineering --- Engineering analysis --- Mathematics

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This latest volume in the Wavelets Analysis and Its Applications Series provides significant and up-to-date insights into recent developments in the field of wavelet constructions in connection with partial differential equations. Specialists in numerical applications and engineers in a variety of fields will find Multiscale Wavelet for Partial Differential Equations to be a valuable resource. Key Features * Covers important areas of computational mechanics such as elasticity and computational fluid dynamics * Includes a clear study of turbulence modeling * Contains recent research on multiresolution analyses with operator-adapted wavelet discretizations * Presents well-documented numerical experiments connected with the development of algorithms, useful in specific applications.

Numerical solutions of differential equations

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This volume is dedicated to the fundamentals of convex functional analysis. It presents those aspects of functional analysis that are extensively used in various applications to mechanics and control theory. The purpose of the text is essentially two-fold. On the one hand, a bare minimum of the theory required to understand the principles of functional, convex and set-valued analysis is presented. Numerous examples and diagrams provide as intuitive an explanation of the principles as possible. On the other hand, the volume is largely self-contained. Those with a background in graduate mathematics will find a concise summary of all main definitions and theorems. Contents: Classical Abstract Spaces in Functional Analysis Linear Functionals and Linear Operators Common Function Spaces in Applications Differential Calculus in Normed Vector Spaces Minimization of Functionals Convex Functionals Lower Semicontinuous Functionals

Engineering sciences. Technology --- systeemtheorie --- systeembeheer

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• Reference Manager
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Robust design that is, managing design uncertainties such as model uncertainty or parametric uncertainty is the often unpleasant issue crucial in much multidisciplinary optimal design work. Recently, there has been enormous practical interest in strategies for applying optimization tools to the development of robust solutions and designs in several areas, including aerodynamics, the integration of sensing (e.g., laser radars, vision-based systems, and millimeter-wave radars) and control, cooperative control with poorly modeled uncertainty, cascading failures in military and civilian applications, multi-mode seekers/sensor fusion, and data association problems and tracking systems. The contributions to this book explore these different strategies. The expression "optimization-directed  in this book's title is meant to suggest that the focus is not agonizing over whether optimization strategies identify a true global optimum, but rather whether these strategies make significant design improvements. Audience

Mathematics --- Engineering sciences. Technology --- Computer. Automation --- toegepaste wiskunde --- automatisering --- systeemtheorie --- systeembeheer