This volume contains more than sixty invited papers of international wellknown scientists in the fields where Alain Bensoussan's contributions have been particularly important: filtering and control of stochastic systems, variationnal problems, applications to economy and finance, numerical analysis... In particular, the extended texts of the lectures of Professors Jens Frehse, Hitashi Ishii, Jacques-Louis Lions, Sanjoy Mitter, Umberto Mosco, Bernt Oksendal, George Papanicolaou, A. Shiryaev, given in the Conference held in Paris on December 4th, 2000 in honor of Professor Alain Bensoussan are included.
This book provides a comprehensive presentation of classical and advanced topics in estimation and control of dynamical systems with an emphasis on stochastic control. Many aspects which are not easily found in a single text are provided, such as connections between control theory and mathematical finance, as well as differential games. The book is self-contained and prioritizes concepts rather than full rigor, targeting scientists who want to use control theory in their research in applied mathematics, engineering, economics, and management science. Examples and exercises are included throughout, which will be useful for PhD courses and graduate courses in general. Dr. Alain Bensoussan is Lars Magnus Ericsson Chair at UT Dallas and Director of the International Center for Decision and Risk Analysis which develops risk management research as it pertains to large-investment industrial projects that involve new technologies, applications and markets. He is also Chair Professor at City University Hong Kong.
Mean field games and Mean field type control introduce new problems in Control Theory. The terminology “games” may be confusing. In fact they are control problems, in the sense that one is interested in a single decision maker, whom we can call the representative agent. However, these problems are not standard, since both the evolution of the state and the objective functional is influenced but terms which are not directly related to the state or the control of the decision maker. They are however, indirectly related to him, in the sense that they model a very large community of agents similar to the representative agent. All the agents behave similarly and impact the representative agent. However, because of the large number an aggregation effect takes place. The interesting consequence is that the impact of the community can be modeled by a mean field term, but when this is done, the problem is reduced to a control problem.
This unified, revised second edition of a two-volume set is a self-contained account of quadratic cost optimal control for a large class of infinite-dimensional systems. The original editions received outstanding reviews, yet this new edition is more concise and self-contained. New material has been added to reflect the growth in the field over the past decade. There is a unique chapter on semigroup theory of linear operators that brings together advanced concepts and techniques which are usually treated independently. The material on delay systems and structural operators has not yet appeared anywhere in book form.
RELIABILITY PREDICTION FOR MICROELECTRONICS Wiley Series in Quality & Reliability Engineering REVOLUTIONIZE YOUR APPROACH TO RELIABILITY ASSESSMENT WITH THIS GROUNDBREAKING BOOK Reliability evaluation is a critical aspect of engineering, without which safe performance within desired parameters over the lifespan of machines cannot be guaranteed. With microelectronics in particular, the challenges to evaluating reliability are considerable, and statistical methods for creating microelectronic reliability standards are complex. With nano-scale microelectronic devices increasingly prominent in modern life, it has never been more important to understand the tools available to evaluate reliability. Reliability Prediction for Microelectronics meets this need with a cluster of tools built around principles of reliability physics and the concept of remaining useful life (RUL). It takes as its core subject the ‘physics of failure’, combining a thorough understanding of conventional approaches to reliability evaluation with a keen knowledge of their blind spots. It equips engineers and researchers with the capacity to overcome decades of errant reliability physics and place their work on a sound engineering footing. Reliability Prediction for Microelectronics readers will also find: Focus on the tools required to perform reliability assessments in real operating conditions Detailed discussion of topics including failure foundation, reliability testing, acceleration factor calculation, and more New multi-physics of failure on DSM technologies, including TDDB, EM, HCI, and BTI Reliability Prediction for Microelectronics is ideal for reliability and quality engineers, design engineers, and advanced engineering students looking to understand this crucial area of product design and testing.
This book collects many helpful techniques for obtaining regularity results for solutions of nonlinear systems of partial differential equations. These are applied in various cases to provide useful examples and relevant results, particularly in such fields as fluid mechanics, solid mechanics, semiconductor theory and game theory.
This is a reprinting of a book originally published in 1978. At that time it was the first book on the subject of homogenization, which is the asymptotic analysis of partial differential equations with rapidly oscillating coefficients, and as such it sets the stage for what problems to consider and what methods to use, including probabilistic methods. At the time the book was written the use of asymptotic expansions with multiple scales was new, especially their use as a theoretical tool, combined with energy methods and the construction of test functions for analysis with weak convergence methods. Before this book, multiple scale methods were primarily used for non-linear oscillation problems in the applied mathematics community, not for analyzing spatial oscillations as in homogenization. In the current printing a number of minor corrections have been made, and the bibliography was significantly expanded to include some of the most important recent references. This book gives systematic introduction of multiple scale methods for partial differential equations, including their original use for rigorous mathematical analysis in elliptic, parabolic, and hyperbolic problems, and with the use of probabilistic methods when appropriate. The book continues to be interesting and useful to readers of different backgrounds, both from pure and applied mathematics, because of its informal style of introducing the multiple scale methodology and the detailed proofs.
This book collects many helpful techniques for obtaining regularity results for solutions of nonlinear systems of partial differential equations. These are applied in various cases to provide useful examples and relevant results, particularly in such fields as fluid mechanics, solid mechanics, semiconductor theory and game theory.
This volume contains the proceedings of the International Conference on Research in Computer Science and Control, held on the occasion of the 25th anniversary of INRIA in December 1992. The objective of this conference was to bring together a large number of the world's leading specialists in information technology who are particularly active in the fields covered by INRIA research programmes, to present the state of the art and a prospective view of future research. The contributions in the volume are organized into the following areas: Parallel processing, databases, networks, and distributed systems; Symbolic computation, programming, and software engineering; Artificial intelligence, cognitive systems, and man-machine interaction; Robotics, image processing, and computer vision; Signal processing, control and manufacturing automation; Scientific computing, numerical software, and computer aided engineering.
The problem of stochastic control of partially observable systems plays an important role in many applications. All real problems are in fact of this type, and deterministic control as well as stochastic control with full observation can only be approximations to the real world. This justifies the importance of having a theory as complete as possible, which can be used for numerical implementation. This book first presents those problems under the linear theory that may be dealt with algebraically. Later chapters discuss the nonlinear filtering theory, in which the statistics are infinite dimensional and thus, approximations and perturbation methods are developed.
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