Exercise Solutions to Accompany Probability and Random Processes PDF Download
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Author: Amedeo O'Doni
Publisher:
ISBN:
Category : Probabilities
Languages : en
Pages : 434
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Book Description
Author: Amedeo O'Doni
Publisher:
ISBN:
Category : Probabilities
Languages : en
Pages : 434
Get Book Here
Book Description
Author: Athanasios Papoulis
Publisher: McGraw-Hill Education
ISBN: 9780071226615
Category : Mathematics
Languages : en
Pages : 852
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Book Description
The fourth edition of Probability, Random Variables and Stochastic Processes has been updated significantly from the previous edition, and it now includes co-author S. Unnikrishna Pillai of Polytechnic University. The book is intended for a senior/graduate level course in probability and is aimed at students in electrical engineering, math, and physics departments. The authors' approach is to develop the subject of probability theory and stochastic processes as a deductive discipline and to illustrate the theory with basic applications of engineering interest. Approximately 1/3 of the text is new material--this material maintains the style and spirit of previous editions. In order to bridge the gap between concepts and applications, a number of additional examples have been added for further clarity, as well as several new topics.
Author: Alberto Leon-Garcia
Publisher: Prentice Hall
ISBN: 0131471228
Category : Electric engineering
Languages : en
Pages : 833
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Book Description
While helping students to develop their problem-solving skills, the author motivates students with practical applications from various areas of ECE that demonstrate the relevance of probability theory to engineering practice.
Author: Dirk P. Kroese
Publisher: John Wiley & Sons
ISBN: 0470285303
Category : Mathematics
Languages : en
Pages : 204
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Book Description
This accessible new edition explores the major topics in Monte Carlo simulation Simulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo Variance reduction techniques such as the transform likelihood ratio method and the screening method The score function method for sensitivity analysis The stochastic approximation method and the stochastic counter-part method for Monte Carlo optimization The cross-entropy method to rare events estimation and combinatorial optimization Application of Monte Carlo techniques for counting problems, with an emphasis on the parametric minimum cross-entropy method An extensive range of exercises is provided at the end of each chapter, with more difficult sections and exercises marked accordingly for advanced readers. A generous sampling of applied examples is positioned throughout the book, emphasizing various areas of application, and a detailed appendix presents an introduction to exponential families, a discussion of the computational complexity of stochastic programming problems, and sample MATLAB® programs. Requiring only a basic, introductory knowledge of probability and statistics, Simulation and the Monte Carlo Method, Second Edition is an excellent text for upper-undergraduate and beginning graduate courses in simulation and Monte Carlo techniques. The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method.
Author: Bruce Hajek
Publisher: Cambridge University Press
ISBN: 1316241246
Category : Technology & Engineering
Languages : en
Pages : 429
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Book Description
This engaging introduction to random processes provides students with the critical tools needed to design and evaluate engineering systems that must operate reliably in uncertain environments. A brief review of probability theory and real analysis of deterministic functions sets the stage for understanding random processes, whilst the underlying measure theoretic notions are explained in an intuitive, straightforward style. Students will learn to manage the complexity of randomness through the use of simple classes of random processes, statistical means and correlations, asymptotic analysis, sampling, and effective algorithms. Key topics covered include: • Calculus of random processes in linear systems • Kalman and Wiener filtering • Hidden Markov models for statistical inference • The estimation maximization (EM) algorithm • An introduction to martingales and concentration inequalities. Understanding of the key concepts is reinforced through over 100 worked examples and 300 thoroughly tested homework problems (half of which are solved in detail at the end of the book).
Author: Athanasios Papoulis
Publisher: Pearson
ISBN:
Category : Computers
Languages : en
Pages : 474
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Book Description
A developed, complete treatment of undergraduate probability and statistics by a very well known author. The approach develops a unified theory presented with clarity and economy. Included many examples and applications. Appropriate for an introductory undergraduate course in probability and statistics for students in engineering, math, the physical sciences, and computer science.(vs. Walpole/Myers, Miller/Freund, Devore, Scheaffer/McClave, Milton/Arnold)
Author: C. A. Trapp
Publisher: Macmillan
ISBN: 9780199288809
Category : Science
Languages : en
Pages : 380
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Book Description
The Solutions manual to accompany Elements of Physical Chemistry 4e contains full worked solutions to all end-of-chapter exercises featured in the book.
Author: Daniel Hartl
Publisher: Jones & Bartlett Publishers
ISBN: 1449644708
Category : Science
Languages : en
Pages : 401
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Book Description
This must-have student resource contains complete solutions to all end-of-chapter problems in Genetics: Analysis of Genes and Genomes, Eighth Edition, by Daniel L. Hartl and Maryellen Ruvolo, as well as a wealth of supplemental problems and exercises with full solutions, a complete chapter summary, and keyword section. The supplemental problems provided in this manual are designed as learning opportunities rather than exercises to be completed by rote. They are organized into chapters that parallel those of the main text, and all problems can be solved through application of the concepts and principles explained in Genetics, Eighth Edition.
Author: Zdzislaw Brzezniak
Publisher: Springer Science & Business Media
ISBN: 9783540761754
Category : Mathematics
Languages : en
Pages : 244
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Book Description
Stochastic processes are tools used widely by statisticians and researchers working in the mathematics of finance. This book for self-study provides a detailed treatment of conditional expectation and probability, a topic that in principle belongs to probability theory, but is essential as a tool for stochastic processes. The book centers on exercises as the main means of explanation.
Author: René L. Schilling
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110307308
Category : Mathematics
Languages : en
Pages : 424
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Book Description
Brownian motion is one of the most important stochastic processes in continuous time and with continuous state space. Within the realm of stochastic processes, Brownian motion is at the intersection of Gaussian processes, martingales, Markov processes, diffusions and random fractals, and it has influenced the study of these topics. Its central position within mathematics is matched by numerous applications in science, engineering and mathematical finance. Often textbooks on probability theory cover, if at all, Brownian motion only briefly. On the other hand, there is a considerable gap to more specialized texts on Brownian motion which is not so easy to overcome for the novice. The authors’ aim was to write a book which can be used as an introduction to Brownian motion and stochastic calculus, and as a first course in continuous-time and continuous-state Markov processes. They also wanted to have a text which would be both a readily accessible mathematical back-up for contemporary applications (such as mathematical finance) and a foundation to get easy access to advanced monographs. This textbook, tailored to the needs of graduate and advanced undergraduate students, covers Brownian motion, starting from its elementary properties, certain distributional aspects, path properties, and leading to stochastic calculus based on Brownian motion. It also includes numerical recipes for the simulation of Brownian motion.
