Introduction to Random Processes PDF Download

Author: E. Wong
Publisher: Springer Science & Business Media
ISBN: 1475717954
Category : Mathematics
Languages : en
Pages : 183

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Author: William A. Gardner
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 456

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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: William A. Gardner
Publisher: McGraw-Hill Companies
ISBN: 9780070228559
Category : Mathematics
Languages : en
Pages : 546

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Author: A. V. Balakrishnan
Publisher: Wiley-Interscience
ISBN:
Category : Mathematics
Languages : en
Pages : 420

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Book Description
Breaking with the traditional treatment of random processes in engineering On the surface, Introduction to Random Processes in Engineering is simply a first-rate textbook for senior or first-year graduate engineering courses in stochastic processes. A closer look, however, reveals an innovative book—rich with examples and commonsense explanations—that demystifies theories, eliminates ambiguities, and provides a solid, up-to-date introduction to this important subject. Departing from the classical texts of the sixties and seventies in its coverage of random signals and data processing, Introduction to Random Processes in Engineering addresses the latest advances in communication, control engineering, and signal processing by allowing all processes to be multidimensional with an emphasis on discrete-time processes and systems. Unlike current texts, this volume provides a strong mathematical perspective for its engineering topics without getting bogged down in technicalities. It employs mathematics to achieve clarity and precision, and at times even uses the theorem/proof style to emphasize mathematical fine points. This approach is particularly advantageous when dealing with random data, and when building an understanding of the many computer programs routinely used, its theoretical principles, and the results it generates. Assuming a senior-level background in probability theory and some acquaintance with linear systems and signals, the book provides: A review chapter of the formulas used later in the book Illustrative examples Emphasis in simulation techniques Problems accompanying each chapter that often introduce the student to other relevant material Notes and comments following each chapter that encourage additional reading as well as historical explorations in the field Tips for using the material at various levels of instruction With its logical and systematically ordered presentation of the material, as well as its fresh approach, Introduction to Random Processes in Engineering is both a superior textbook and a valuable reference for practicing engineers and researchers in the field.

Author: John A. Gubner
Publisher: Cambridge University Press
ISBN: 1139457179
Category : Technology & Engineering
Languages : en
Pages : 4

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Book Description
The theory of probability is a powerful tool that helps electrical and computer engineers to explain, model, analyze, and design the technology they develop. The text begins at the advanced undergraduate level, assuming only a modest knowledge of probability, and progresses through more complex topics mastered at graduate level. The first five chapters cover the basics of probability and both discrete and continuous random variables. The later chapters have a more specialized coverage, including random vectors, Gaussian random vectors, random processes, Markov Chains, and convergence. Describing tools and results that are used extensively in the field, this is more than a textbook; it is also a reference for researchers working in communications, signal processing, and computer network traffic analysis. With over 300 worked examples, some 800 homework problems, and sections for exam preparation, this is an essential companion for advanced undergraduate and graduate students. Further resources for this title, including solutions (for Instructors only), are available online at www.cambridge.org/9780521864701.

Author: Wim C. Van Etten
Publisher: John Wiley & Sons
ISBN: 0470024127
Category : Science
Languages : en
Pages : 270

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Book Description
Random signals and noise are present in many engineering systems and networks. Signal processing techniques allow engineers to distinguish between useful signals in audio, video or communication equipment, and interference, which disturbs the desired signal. With a strong mathematical grounding, this text provides a clear introduction to the fundamentals of stochastic processes and their practical applications to random signals and noise. With worked examples, problems, and detailed appendices, Introduction to Random Signals and Noise gives the reader the knowledge to design optimum systems for effectively coping with unwanted signals. Key features: Considers a wide range of signals and noise, including analogue, discrete-time and bandpass signals in both time and frequency domains. Analyses the basics of digital signal detection using matched filtering, signal space representation and correlation receiver. Examines optimal filtering methods and their consequences. Presents a detailed discussion of the topic of Poisson processes and shot noise. An excellent resource for professional engineers developing communication systems, semiconductor devices, and audio and video equipment, this book is also ideal for senior undergraduate and graduate students in Electronic and Electrical Engineering.

Author: James J. Solberg
Publisher: John Wiley & Sons
ISBN: 0470322551
Category : Technology & Engineering
Languages : en
Pages : 320

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Book Description
By reducing mathematical detail and focusing on real-world applications, this book provides engineers with an easy-to-understand overview of stochastic modeling. An entire chapter is included on how to set up the problem, and then another complete chapter presents examples of applications before doing any math. A previously unpublished computational method for solving equations related to Markov processes is added. The book shows how to add costs or revenues to the basic probability structures without much additional effort. In addition, numerous examples are included that show how the theory can be used. Engineers will also find explanations on how to formulate word problems into the models that the math worked on.

Author: Amedeo R. Odoni
Publisher:
ISBN: 9780070475670
Category :
Languages : en
Pages : 415

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Book Description

Author: Oliver Ibe
Publisher: Academic Press
ISBN: 0128010355
Category : Mathematics
Languages : en
Pages : 456

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Book Description
The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book's clear writing style and homework problems make it ideal for the classroom or for self-study. Demonstrates concepts with more than 100 illustrations, including 2 dozen new drawings Expands readers’ understanding of disruptive statistics in a new chapter (chapter 8) Provides new chapter on Introduction to Random Processes with 14 new illustrations and tables explaining key concepts. Includes two chapters devoted to the two branches of statistics, namely descriptive statistics (chapter 8) and inferential (or inductive) statistics (chapter 9).