Buch, Englisch, Band 17, 520 Seiten, Format (B × H): 164 mm x 246 mm, Gewicht: 2090 g
In Honor of Gilbert Strang
Buch, Englisch, Band 17, 520 Seiten, Format (B × H): 164 mm x 246 mm, Gewicht: 2090 g
Reihe: Advances in Mechanics and Mathematics
ISBN: 978-0-387-75713-1
Verlag: Springer
Much of the material, including the various methodologies, is written for nonexperts and is intended to stimulate graduate students and young faculty to venture into this rich domain of research; it will also benefit researchers and practitioners in several areas of applied mathematics, mechanics, and engineering.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
- Mathematik | Informatik EDV | Informatik Technische Informatik Quantencomputer, DNA-Computing
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Informationstheorie, Kodierungstheorie
- Mathematik | Informatik Mathematik Mathematik Allgemein Diskrete Mathematik, Kombinatorik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
Weitere Infos & Material
Maximum Flows and Minimum Cuts in the Plane.- Variational Principles and Residual Bounds for Nonpotential Equations.- Adaptive Finite Element Solution of Variational Inequalities with Application in Contact Problems.- Time—Frequency Analysis of Brain Neurodynamics.- Nonconvex Optimization for Communication Networks.- Multilevel (Hierarchical) Optimization: Complexity Issues, Optimality Conditions, Algorithms.- Central Path Curvature and Iteration-Complexity for Redundant Klee—Minty Cubes.- Canonical Duality Theory: Connections between Nonconvex Mechanics and Global Optimization.- Quantum Computation and Quantum Operations.- Ekeland Duality as a Paradigm.- Global Optimization in Practice:State of the Art and Perspectives.- Two-Stage Stochastic Mixed-Integer Programs: Algorithms and Insights.- Dualistic Riemannian Manifold Structure Induced from Convex Functions.- NMR Quantum Computing.