Minimal Surfaces I is an introduction to the field of minimal surfaces and a presentation of the classical theory as well as of parts of the modern development centered around boundary value problems.
This volume contains the proceedings of the summer school "e;Modern Methods of Optimization"e;, held at the Schlof3 Thurnau of the University of Bayreuth, October 1-6, 1990.
From the reviews to the first edition:Most of the literature about stochastic differentialequations seems to place so much emphasis on rigor andcompleteness that it scares the nonexperts away.
Minimal surfaces I is an introduction to the field ofminimal surfaces and apresentation of the classical theoryas well as of parts of the modern development centeredaround boundary value problems.
The purpose of this book is to present a self-contained description of the fundamentals of the theory of nonlinear control systems, with special emphasis on the differential geometric approach.
In engineering and economics a certain vector of inputs or decisions must often be chosen, subject to some constraints, such that the expected costs arising from the deviation between the output of a stochastic linear system and a desired stochastic target vector are minimal.
The most immediate one-dimensional variation problem is certainly the problem of determining an arc of curve, bounded by two given and having a smallest possible length.
"e;Signal Processing and Systems Theory"e; is concerned with thestudy of H-optimization for digital signal processing anddiscrete-time control systems.
Predation is an ecological factor of almost universal importance for the biol- ogist who aims at an understanding of the habits and structures of animals.
Since the publication of the first edition of our book, geometric algorithms and combinatorial optimization have kept growing at the same fast pace as before.
This monograph deals with various classes of deterministic and stochastic continuous time optimal control problems that are defined over unbounded time intervals.
The primary aim of this monograph is to provide a formal framework for the representation and management of uncertainty and vagueness in the field of artificial intelligence.
Ever since the discovery of the five platonic solids in ancient times, the study of symmetry and regularity has been one of the most fascinating aspects of mathematics.
A knowledge of linear systems provides a firm foundation for the study of optimal control theory and many areas of system theory and signal processing.
Conceived by Count Jacopo Francesco Riccati more than a quarter of a millennium ago, the Riccati equation has been widely studied in the subsequent centuries.
This book is motivated largely by a desire to solve shape optimization prob- lems that arise in applications, particularly in structural mechanics and in the optimal control of distributed parameter systems.
The fields of integer programming and combinatorial optimization continue to be areas of great vitality, with an ever increasing number of publications and journals appearing.
In recent years there has been a considerable renewal of interest in the clas- sical problems of the calculus of variations, both from the point of view of mathematics and of applications.
This volume contains selected papers presented at the "e;International Workshop on Computationally Intensive Methods in Simulation and Op- th th timization"e; held from 23 to 25 August 1990 at the International Institute for Applied Systems Analysis (nASA) in La~enburg, Austria.
The craft of designing mathematical models of dynamic objects offers a large number of methods to solve subproblems in the design, typically parameter estimation, order determination, validation, model reduc- tion, analysis of identifiability, sensi tivi ty and accuracy.
Generalizations of the classical concept of a convexfunction have been proposed in various fields such aseconomics, management science, engineering, statistics andapplied sciences during the second half of this century.
In February 1992, I defended my doctoral thesis: Engineering Optimiza- tion - selected contributions (IMSOR, The Technical University of Den- mark, 1992, p.
