Space Division Multiple Access is one of the most promising methods in solving the capacity problem of wireless communication systems. This book defines formulae that can be used to evaluate the limit
A unique interdisciplinary foundation for real-world problem solvingStochastic search and optimization techniques are used in a vast number of areas, including aerospace, medicine, transportation, and
This book provides an introduction to probability theory and its applications. The emphasis is on essential probabilistic reasoning, which is illustrated with a large number of samples. The fourth edi
Situational and tactical factors, which are usually treated only in complex models, strongly influence the effectiveness of long-range precision weapons in interdicting a moving armored column. This s
This work highlights emergent research in the area of quantum probability. Several papers present a qualitative analysis of quantum dynamical semigroups and new results on q-deformed oscillator algebr
This monograph extends recent methods of analysis of production efficiency by integrating two approaches in measuring the economic performance of firms and industries: data envelopment analysis (DEA)
Optimization problems arising in practice usually contain several random parameters. Hence, in order to obtain optimal solutions being robust with respect to random parameter variations, the mostly av
This book provides a clear and straightforward introduction to applications of probability theory with examples given in the biological sciences and engineering.The first chapter contains a summary of
Both an introduction and a basic reference text on non-Gaussian stable models, for graduate students and practitioners. Assuming only a first-year graduate course in probability, it includes material
This is the third of six volumes collecting significant papers of the distinguished astrophysicist and Nobel laureate S. Chandrasekhar. His work is notable for its breadth as well as for its brillianc
Wiley-Interscience Series in Discrete Mathematics and Optimization Advisory Editors Ronald L. Graham Jan Karel Lenstra Robert E. Tarjan Discrete Mathematics and Optimization involves the study of fini
This book provides a rigorous yet accessible introduction to the theory of stochastic processes. A significant part of the book is devoted to the classic theory of stochastic processes. In turn, it al
This book discusses advanced topics such as R core programing, object oriented R programing, parallel computing with R, and spatial data types. The author leads readers to merge mature and effective m
The objective here is to introduce the elements of stochastic processes in a rather concise manner where we present the two most important parts in stochastic processes — Markov chains and stochastic
As Non-Life Insurance models are strictly connected with stochastic processes, the main aim of this book is to show how classical and recent advanced stochastic models can be used to improve the stoch
Stochastic modeling facilitates an understanding of natural phenomena depicted in medical anatomical and functional (dynamic) MRI and CT images. This textbook details efficient stochastic modeling tec
A comprehensive introduction to the core issues of stochastic differential equations and their effective application Introduction to Stochastic Differential Equations with Applications to Modelling in
The book provides a self-contained treatment of stochastic finite element methods. It helps the reader to establish a solid background on stochastic and reliability analysis of structural systems and
Based on a well-established and popular course taught by the authors over many years, Stochastic Processes: An Introduction, Third Edition, discusses the modelling and analysis of random experiments,
This book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sciences. The main focus is analytical meth
A stochastic flow is a mathematical model used to simulate a system of interacting particles in random media. There have been many developments in methodology and applications in recent years, and thi
This text focuses on the parts of stochastic theory that are particularly relevant to applications. It begins with a description of Brownian motion and the associated stochastic calculus, including th
Stochastic processes are necessary ingredients for building models of a wide variety of phenomena exhibiting time varying randomness. This text offers easy access to this fundamental topic for many st
The systematic study of existence, uniqueness, and properties of solutions to stochastic differential equations in infinite dimensions arising from practical problems characterizes this volume that is
This volume provides a general overview of discrete- and continuous-time Markov control processes and stochastic games, along with a look at the range of applications of stochastic control and some of
"Several approaches have been used to develop the concept of stochastic calculus for fBm. The purpose of this book is to present a comprehensive account of the different definitions of stochastic inte
This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a
Stochastic portfolio theory is a mathematical methodology for constructing stock portfolios and for analyzing the effects induced on the behavior of these portfolios by changes in the distribution of
Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using
Like its widely praised, best-selling predecessor, Pattern Theory: The Stochastic Analysis of Real-World Signals, Second Edition treats the mathematical tools, the models themselves, and the computati
Stochastic Analysis of Mixed Fractional Gaussian Processes presents the main tools necessary to characterize Gaussian processes. The book focuses on the particular case of the linear combination of in
This text introduces engineering students to probability theory and stochastic processes. Along with thorough mathematical development of the subject, the book presents intuitive explanations of key p
This is the first book designed to introduce Bayesian inference procedures for stochastic processes. There are clear advantages to the Bayesian approach (including the optimal use of prior information
This book provides a comprehensive introduction to the theory of stochastic calculus and some of its applications. It is the only textbook on the subject to include more than two hundred exercises wit
This book brings together the latest findings in the area of stochastic analysis and statistics. The individual chapters cover a wide range of topics from limit theorems, Markov processes, nonparametr
