Introduction to Random Processes
Author: William A. Gardner
Publisher:
Published: 1986
Total Pages: 456
ISBN-13:
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Author: William A. Gardner
Publisher:
Published: 1986
Total Pages: 456
ISBN-13:
DOWNLOAD EBOOKAuthor: Iosif Il?ich Gikhman
Publisher: Courier Corporation
Published: 1996-01-01
Total Pages: 537
ISBN-13: 0486693872
DOWNLOAD EBOOKRigorous exposition suitable for elementary instruction. Covers measure theory, axiomatization of probability theory, processes with independent increments, Markov processes and limit theorems for random processes, more. A wealth of results, ideas, and techniques distinguish this text. Introduction. Bibliography. 1969 edition.
Author: Erhan Cinlar
Publisher: Courier Corporation
Published: 2013-02-20
Total Pages: 418
ISBN-13: 0486276325
DOWNLOAD EBOOKClear presentation employs methods that recognize computer-related aspects of theory. Topics include expectations and independence, Bernoulli processes and sums of independent random variables, Markov chains, renewal theory, more. 1975 edition.
Author: William A. Gardner
Publisher: McGraw-Hill Companies
Published: 1990-01
Total Pages: 546
ISBN-13: 9780070228559
DOWNLOAD EBOOKAuthor: Oliver Ibe
Publisher: Academic Press
Published: 2014-06-13
Total Pages: 457
ISBN-13: 0128010355
DOWNLOAD EBOOKThe 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).
Author: Bruce Hajek
Publisher: Cambridge University Press
Published: 2015-03-12
Total Pages: 429
ISBN-13: 1316241246
DOWNLOAD EBOOKThis 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: E. Wong
Publisher: Springer Science & Business Media
Published: 2013-03-09
Total Pages: 183
ISBN-13: 1475717954
DOWNLOAD EBOOKAuthor: Hossein Pishro-Nik
Publisher:
Published: 2014-08-15
Total Pages: 746
ISBN-13: 9780990637202
DOWNLOAD EBOOKThe 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: Scott Miller
Publisher: Academic Press
Published: 2012-01-11
Total Pages: 625
ISBN-13: 0123869811
DOWNLOAD EBOOKMiller 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: Nikolaĭ Vladimirovich Krylov
Publisher: American Mathematical Soc.
Published: 2002
Total Pages: 245
ISBN-13: 0821829858
DOWNLOAD EBOOKThis book concentrates on some general facts and ideas of the theory of stochastic processes. The topics include the Wiener process, stationary processes, infinitely divisible processes, and Ito stochastic equations. Basics of discrete time martingales are also presented and then used in one way or another throughout the book. Another common feature of the main body of the book is using stochastic integration with respect to random orthogonal measures. In particular, it is used forspectral representation of trajectories of stationary processes and for proving that Gaussian stationary processes with rational spectral densities are components of solutions to stochastic equations. In the case of infinitely divisible processes, stochastic integration allows for obtaining arepresentation of trajectories through jump measures. The Ito stochastic integral is also introduced as a particular case of stochastic integrals with respect to random orthogonal measures. Although it is not possible to cover even a noticeable portion of the topics listed above in a short book, it is hoped that after having followed the material presented here, the reader will have acquired a good understanding of what kind of results are available and what kind of techniques are used toobtain them. With more than 100 problems included, the book can serve as a text for an introductory course on stochastic processes or for independent study. Other works by this author published by the AMS include, Lectures on Elliptic and Parabolic Equations in Holder Spaces and Introduction to the Theoryof Diffusion Processes.