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Author: D N Shanbhag Publisher: Gulf Professional Publishing ISBN: 9780444500137 Category : Computers Languages : en Pages : 1028
Book Description
This sequel to volume 19 of Handbook on Statistics on Stochastic Processes: Modelling and Simulation is concerned mainly with the theme of reviewing and, in some cases, unifying with new ideas the different lines of research and developments in stochastic processes of applied flavour. This volume consists of 23 chapters addressing various topics in stochastic processes. These include, among others, those on manufacturing systems, random graphs, reliability, epidemic modelling, self-similar processes, empirical processes, time series models, extreme value therapy, applications of Markov chains, modelling with Monte Carlo techniques, and stochastic processes in subjects such as engineering, telecommunications, biology, astronomy and chemistry. particular with modelling, simulation techniques and numerical methods concerned with stochastic processes. The scope of the project involving this volume as well as volume 19 is already clarified in the preface of volume 19. The present volume completes the aim of the project and should serve as an aid to students, teachers, researchers and practitioners interested in applied stochastic processes.
Author: D N Shanbhag Publisher: Gulf Professional Publishing ISBN: 9780444500137 Category : Computers Languages : en Pages : 1028
Book Description
This sequel to volume 19 of Handbook on Statistics on Stochastic Processes: Modelling and Simulation is concerned mainly with the theme of reviewing and, in some cases, unifying with new ideas the different lines of research and developments in stochastic processes of applied flavour. This volume consists of 23 chapters addressing various topics in stochastic processes. These include, among others, those on manufacturing systems, random graphs, reliability, epidemic modelling, self-similar processes, empirical processes, time series models, extreme value therapy, applications of Markov chains, modelling with Monte Carlo techniques, and stochastic processes in subjects such as engineering, telecommunications, biology, astronomy and chemistry. particular with modelling, simulation techniques and numerical methods concerned with stochastic processes. The scope of the project involving this volume as well as volume 19 is already clarified in the preface of volume 19. The present volume completes the aim of the project and should serve as an aid to students, teachers, researchers and practitioners interested in applied stochastic processes.
Author: Carl Graham Publisher: Springer Science & Business Media ISBN: 3642393632 Category : Mathematics Languages : en Pages : 264
Book Description
In various scientific and industrial fields, stochastic simulations are taking on a new importance. This is due to the increasing power of computers and practitioners’ aim to simulate more and more complex systems, and thus use random parameters as well as random noises to model the parametric uncertainties and the lack of knowledge on the physics of these systems. The error analysis of these computations is a highly complex mathematical undertaking. Approaching these issues, the authors present stochastic numerical methods and prove accurate convergence rate estimates in terms of their numerical parameters (number of simulations, time discretization steps). As a result, the book is a self-contained and rigorous study of the numerical methods within a theoretical framework. After briefly reviewing the basics, the authors first introduce fundamental notions in stochastic calculus and continuous-time martingale theory, then develop the analysis of pure-jump Markov processes, Poisson processes, and stochastic differential equations. In particular, they review the essential properties of Itô integrals and prove fundamental results on the probabilistic analysis of parabolic partial differential equations. These results in turn provide the basis for developing stochastic numerical methods, both from an algorithmic and theoretical point of view. The book combines advanced mathematical tools, theoretical analysis of stochastic numerical methods, and practical issues at a high level, so as to provide optimal results on the accuracy of Monte Carlo simulations of stochastic processes. It is intended for master and Ph.D. students in the field of stochastic processes and their numerical applications, as well as for physicists, biologists, economists and other professionals working with stochastic simulations, who will benefit from the ability to reliably estimate and control the accuracy of their simulations.
Author: Scott Miller Publisher: Academic Press ISBN: 0123869811 Category : Mathematics Languages : en Pages : 625
Book Description
Miller and Childers have focused on creating a clear presentation of foundational concepts with specific applications to signal processing and communications, clearly the two areas of most interest to students and instructors in this course. It is aimed at graduate students as well as practicing engineers, and includes unique chapters on narrowband random processes and simulation techniques. The appendices provide a refresher in such areas as linear algebra, set theory, random variables, and more. Probability and Random Processes also includes applications in digital communications, information theory, coding theory, image processing, speech analysis, synthesis and recognition, and other fields. * Exceptional exposition and numerous worked out problems make the book extremely readable and accessible * The authors connect the applications discussed in class to the textbook * The new edition contains more real world signal processing and communications applications * Includes an entire chapter devoted to simulation techniques.
Author: J. Cacko Publisher: Elsevier ISBN: 0444598030 Category : Technology & Engineering Languages : en Pages : 245
Book Description
This book covers the basic topics associated with the measurement, analysis and simulation of random environmental processes which are encountered in practice when dealing with the dynamics, fatigue and reliability of structures in real environmental conditions. The treatment is self-contained and the authors have brought together and integrated the most important information relevant to this topic in order that the newcomer can see and study it as a whole. This approach should also be of interest to experienced engineers from fatigue laboratories who want to learn more about the possible methods of simulation, especially for use in real time on electrohydraulic computer-controlled loading machines.Problems of constructing a measuring system are dealt with in the first chapter. Here the authors discuss the choice of measuring conditions and locations, as well as the organization of a chain of devices for measuring and recording random environmental processes. Some experience gained from practical measurements is also presented. The recorded processes are further analysed by various methods. The choice is governed by the aims of the measurements and applications of the results. Chapter 2 is thus devoted to methods of random process evaluations for digital computers, both from the fatigue and dynamic point of view. The most important chapter is Chapter 3 as this presents a review of up-to-date methods of random process simulation with given statistical characteristics. These methods naturally follow those of random process analysis, and their results form initial data for the corresponding simulations algorithms, including occurrences of characteristic parameters of counting methods, reproduction of correlation theory characteristics and of autoregressive models. The simulation of non-stationary processes is treated in depth, taking into account their importance for practical applications and also the lack of information of this subject.The book is intended to help resolve many practical problems concerning the methods and quality of environmental process evaluation and simulation which can arise when up-to-date loading systems with computer control are being used in material, component and structural fatigue and dynamic research.
Author: Steven Kay Publisher: Springer Science & Business Media ISBN: 0387241582 Category : Technology & Engineering Languages : en Pages : 838
Book Description
Intuitive Probability and Random Processes using MATLAB® is an introduction to probability and random processes that merges theory with practice. Based on the author’s belief that only "hands-on" experience with the material can promote intuitive understanding, the approach is to motivate the need for theory using MATLAB examples, followed by theory and analysis, and finally descriptions of "real-world" examples to acquaint the reader with a wide variety of applications. The latter is intended to answer the usual question "Why do we have to study this?" Other salient features are: *heavy reliance on computer simulation for illustration and student exercises *the incorporation of MATLAB programs and code segments *discussion of discrete random variables followed by continuous random variables to minimize confusion *summary sections at the beginning of each chapter *in-line equation explanations *warnings on common errors and pitfalls *over 750 problems designed to help the reader assimilate and extend the concepts Intuitive Probability and Random Processes using MATLAB® is intended for undergraduate and first-year graduate students in engineering. The practicing engineer as well as others having the appropriate mathematical background will also benefit from this book. About the Author Steven M. Kay is a Professor of Electrical Engineering at the University of Rhode Island and a leading expert in signal processing. He has received the Education Award "for outstanding contributions in education and in writing scholarly books and texts..." from the IEEE Signal Processing society and has been listed as among the 250 most cited researchers in the world in engineering.
Author: Roger D. Peng Publisher: ISBN: 9781365056826 Category : R (Computer program language) Languages : en Pages : 0
Book Description
Data science has taken the world by storm. Every field of study and area of business has been affected as people increasingly realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it an invaluable tool for data scientists around the world. This book is about the fundamentals of R programming. You will get started with the basics of the language, learn how to manipulate datasets, how to write functions, and how to debug and optimize code. With the fundamentals provided in this book, you will have a solid foundation on which to build your data science toolbox.
Author: Volker Schmidt Publisher: Springer ISBN: 3319100645 Category : Mathematics Languages : en Pages : 484
Book Description
This volume is an attempt to provide a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, with special emphasis placed on fundamental classes of models and algorithms as well as on their applications, e.g. in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R which are widely used in the mathematical community. It can be seen as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered with a focus on asymptotic methods.
Author: Hossein Pishro-Nik Publisher: ISBN: 9780990637202 Category : Probabilities Languages : en Pages : 746
Book Description
The book covers basic concepts such as random experiments, probability axioms, conditional probability, and counting methods, single and multiple random variables (discrete, continuous, and mixed), as well as moment-generating functions, characteristic functions, random vectors, and inequalities; limit theorems and convergence; introduction to Bayesian and classical statistics; random processes including processing of random signals, Poisson processes, discrete-time and continuous-time Markov chains, and Brownian motion; simulation using MATLAB and R.
Author: D N Shanbhag
Author: D N Shanbhag
Author: Carl Graham
Author: Scott Miller
Author: J. Cacko
Author: Steven Kay
Author: Roger D. Peng
Author: V. A. Ogorodnikov
Author: Aleksand Janicki
Author: Volker Schmidt
Author: Hossein Pishro-Nik