Описание: Develops the basic mathematical theory of the finite element method, the most widely used technique for engineering design and analysis. This book provides an introduction to basic functional analysis, approximation theory, and numerical analysis, while building upon and applying basic techniques of real variable theory.
Описание: Thesubjectofthisbookisthemodelingofcomplex systemsinthelife sciences constituted by a large number of interacting entities called active particles. Their physical state includes, in addition to geometrical and mechanical variables, a variable called the activity, which characterizes the speci?c living system to be modeled. Interactions among particles not only modify the microscopic state, but may generate proliferative and/or destructive phenomena. The aim of the book is to develop mathematical methods and tools, even a new mathematics, for the modeling of living systems. The background idea is that the modeling of living systems requires technically complex mathematical methods, which may be s- stantially di?erent from those used to deal with inert matter. The?rstpart ofthe bookdiscussesmethodological issues, namely the derivation of various general mathematical frameworks suitable to model particular systems of interest in the applied sciences. The second part presents the various models and applications. The mathematical approach used in the book is based on mathema- cal kinetic theoryfor active particles, whichleads tothederivation of evo- tion equations for a one-particle distribution function over the microscopic state. Two types of equations, to be regarded as a general mathematical framework for deriving the models, are derived corresponding to short and long range interactions.
Автор: BГјhlmann Hans Название: Mathematical Methods in Risk Theory. ISBN: 3540051171 ISBN-13(EAN): 9783540051176 Издательство: Springer Рейтинг: Цена: 8672 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: From the reviews: "... a masterful work.." Transactions, Soc of Actuaries Meetings 65"The huge literature in risk theory has been carefully selected and supplemented by personal contributions of the author, many of which appear here for the first time. The result is a systematic and very readable book, which takes into account the most recent developments of the field. It will be of great interest to the actuary as well as to the statistician who wants to become familiar with the subject." Math. Reviews Vol. 43"..., the book (and its author) had enormous impact on the development of risk theory. It was the first self-contained monograph on risk theory providing a rigorous probabilistic foundation. ...[and]... made an important contribution to the successful development of risk theory. This success has made the book a classic." Zentralblatt MATH, 1996
Описание: This book describes the evolution of several socio-biological systems using mathematical kinetic theory. It is one of the first books to apply mathematical kinetic theory to biological systems. Specifically, it deals with modeling and simulations of biological systems.
Автор: Fuente, Angel de la. Название: Mathematical methods and models for economists ISBN: 0521585295 ISBN-13(EAN): 9780521585293 Издательство: Cambridge Academ Рейтинг: Цена: 5406 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is intended as a textbook for a first-year PhD course in mathematics for economists and as a reference for graduate students in economics. It provides a self-contained, rigorous treatment of most of the concepts and techniques required to follow the standard first-year theory sequence in micro and macroeconomics. The topics covered include an introduction to analysis in metric spaces, differential calculus, comparative statics, convexity, static optimization, dynamical systems and dynamic optimization. The book includes a large number of applications to standard economic models and over two hundred fully worked-out problems.
Описание: Presents basic optimization principles and gradient-based algorithms to a general audience. This work pays attention to the difficulties - such as noise, discontinuities, expense of function evaluations, and the existence of multiple minima - that often unnecessarily inhibit the use of gradient-based methods.
Автор: Osborne Название: An Introduction to Game Theory ISBN: 0195322487 ISBN-13(EAN): 9780195322484 Издательство: Oxford Academ Рейтинг: Цена: 6326 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Game-theoretic reasoning pervades economic theory and is used widely in other social and behavioural sciences. An Introduction to Game Theory International Edition, by Martin J. Osborne, presents the main principles of game theory and shows how they can be used to understand economics, social, political, and biological phenomena. The book introduces in an accessible manner the main ideas behind the theory rather than their mathematical expression. All concepts are defined precisely, and logical reasoning is used throughout. The book requires an understanding of basic mathematics but assumes no specific knowledge of economics, political science, or other social or behavioural sciences. Coverage includes the fundamental concepts of strategic games, extensive games with perfect information, and coalitional games; the more advanced subjects of Bayesian games and extensive games with imperfect information; and the topics of repeated games, bargaining theory, evolutionary equilibrium, rationalizability, and maxminimization. The book offers a wide variety of illustrations from the social and behavioural sciences. Each topic features examples that highlight theoretical points and illustrations that demonstrate how the theory may be used.
Автор: Sundaram, Rangarajan K. Название: A First Course in Optimization Theory ISBN: 0521497701 ISBN-13(EAN): 9780521497701 Издательство: Cambridge Academ Рейтинг: Цена: 4025 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces students to optimization theory and its use in economics and allied disciplines.
Описание: This volume provides a compilation of recent contributions on feedback and robust control, modeling, estimation and filtering. They were presented on the occasion of the sixtieth birthday of Anders Lindquist, who has delivered fundamental contributions to the fields of systems, signals and control for more than three decades. His contributions include seminal work on the role of splitting subspaces in stochastic realization theory, on the partial realization problem for both deterministic and stochastic systems, on the solution of the rational covariance extension problem and on system identification. Lindquist's research includes the development of fast filtering algorithms, leading to a nonlinear dynamical system which computes spectral factors in its steady state, and which provide an alternate, linear in the dimension of the state space, to computing the Kalman gain from a matrix Riccati equation. He established the separation principle for stochastic function differential equations, including some fundamental work on optimal control for stochastic systems with time lags. His recent work on a complete parameterization of all rational solutions to the Nevanlinna-Pick problem is providing a new approach to robust control design.
Описание: This book presents basic optimization principles and gradient-based algorithms to a general audience in a brief and easy-to-read form, without neglecting rigor. The work should enable professionals to apply optimization theory and algorithms to their own particular practical fields of interest, be it engineering, physics, chemistry, or business economics. Most importantly, for the first time in a relatively brief and introductory work, due attention is paid to the difficulties вЂ“ such as noise, discontinuities, expense of function evaluations, and the existence of multiple minima вЂ“ that often unnecessarily inhibit the use of gradient-based methods. In a separate chapter on new gradient-based methods developed by the author and his coworkers, it is shown how these difficulties may be overcome without losing the desirable features of classical gradient-based methods.