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Probability and Random Processes with Applications to Signal Processing by John W. Woods and Henry Stark (2001, Hardcover)

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Product Information

For courses in Probability and Random Processes. This book is a comprehensive treatment of probability and random processes that, more than any other available source, combines rigor with accessibility . Beginning with the fundamentals of probability theory and requiring only college-level calculus, the book develops all the tools needed to understand more advanced topics such as random sequences (Chapter 6), continuous-time random processes (Chapter 7), and statistical signal processing (Chapter 9). The book progresses at a leisurely pace, never assuming more knowledge than contained in the material already covered. Rigor is established by developing all results from the basic axioms (Chapters 1,2) and carefully defining and discussing such advanced notions as stochastic convergence, stochastic integrals and resolution of stochastic processes (Chapter 8). The 3rd Edition has a large number of new topics, not present in the 2nd Edition, including additional material on basic probability (Appendix B, Section 1.8, Section 1.11), statistics (chi-square and Student-t in Section 2.4, Section 4.1), misuses of probability (Sec. 1.3), and signal processing (all of Chapter 9).

Product Identifiers

Publisher
Prentice Hall PTR
ISBN-10
0130200719
ISBN-13
9780130200716
eBay Product ID (ePID)
1883666

Product Key Features

Author
John w. Woods, Henry Stark
Publication Name
Probability and Random Processes with Applications to Signal Processing
Format
Hardcover
Language
English
Publication Year
2001
Type
Textbook
Number of Pages
699 Pages

Dimensions

Item Length
9.4in
Item Height
1.2in
Item Width
7.2in
Item Weight
40.4 Oz

Additional Product Features

Lc Classification Number
Tk5102.9.S717 2002
Edition Number
3
Table of Content
(NOTE: Each chapter concludes with a Summary, Problems, and References.) 1. Introduction to Probability. Introduction: Why Study Probability? The Different Kinds of Probability. Misuses, Miscalculations, and Paradoxes in Probability. Sets, Fields, and Events. Axiomatic Definition of Probability. Joint, Conditional, and Total Probabilities; Independence. Bayes' Theorem and Applications. Combinatorics. Bernoulli Trials Binomial and Multinomial Laws. Asymptotic Behavior of the Binomial Law: The Poisson Law. Normal Approximation to the Binomial Law. 2. Random Variables. Introduction. Definition of a Random Variable. Probability Distribution Function. Probability Density Function. Continuous, Discrete and Mixed Random Variables. Conditional and Joint Distributions and Densities. Failure Rates. 3. Functions of Random Variables. Introduction. Solving Problems of the Type Y=g(X). Solving Problems of the Type Z=g(X,Y). Solving Problems of the Type V=g(X,Y), W=h(X,Y). Additional Examples. 4. Expectation and Introduction to Estimation. Expected Value of a Random Variable. Conditional Expectation. Moments. Chebyshev and Schwarz Inequalities. Moment Generating Functions. Chernoff Bound. Characteristic Functions. Estimators for the Mean and Variance of the Normal Law. 5. Random Vectors and Parameter Estimation. Joint Distributions and Densities. Multiple Transformation of Random Variables. Expectation Vectors and Covariance Matrices. Properties of Covariance Matrices. Simultaneous Diagonalization of Two Covariance Matrices and Applications in Pattern Recognition. The Multidimensional Gaussian Law. Characteristic Functions of Random Vectors. Parameter Estimation. Estimation of Vector Means and Covariance Matrices. Maximum Likelihood Estimators. Linear Estimation of Vector Parameters. 6. Random Sequences. Basic Concepts. Basic Principles of Discrete-Time Linear Systems. Random Sequences and Linear Systems. WSS Random Sequence. Markov Random Sequences. Vector Random Sequences and State Equations. Convergence of Random Sequences. Laws of Large Numbers. 7. Random Processes. Basic Definitions. Some Important Random Processes. Continuous-Time Linear Systems with Random Inputs. Some Useful Classification of Random Processes. Wide-Sense Stationary Processes and LSI Systems. Periodic and Cyclostationary Processes. Vector Processes and State Equations. 8. Advanced Topics in Random Processes. Mean-Square (m.s.) Calculus. m-s Stochastic Integrals. m-s Stochastic Differential Equations. Ergodicity. Karhunen-Loéve Expansion. Representation of Bandlimited and Periodic Processes. 9. Applications to Statistical Signal Processing. Estimation of Random Variables. Innovation Sequences and Kalman Filtering. Wiener Filter for Random Sequence. Expectation-Maximization Algorithm. Hidden Markov Models (HMM). Spectral Estimation. Simulated Annealing. Appendices. Appendix A: Review of Relevant Mathematics. Basic Mathematics. Continuous Mathematics. Residue Method for Inverse Fourier Transform. Mathematical Induction A-4. Appendix B: Gamma and Delta Functions. Gamma Function. Dirac Delta Function. Appendix C: Functional Transformations and Jacobians. Introduction. Jacobians for n = 2. Jacobian for General n. Appendix D: Measure and Probability. Introduction and Basic Ideas. Application of Measure Theory to Probability. Appendix E: Sampled Analog Waveforms and Discrete-time Signals.
Copyright Date
2002
Target Audience
College Audience
Topic
Signals & Signal Processing, Probability & Statistics / Stochastic Processes, Probability & Statistics / General, Telecommunications
Lccn
2001-021253
Dewey Decimal
519.2
Dewey Edition
21
Illustrated
Yes
Genre
Technology & Engineering, Mathematics

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3.6

3.6 out of 5 stars based on 5 product ratings

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Most relevant reviews

4 out of 5 stars
by optimusprime032...Oct 04, 2006
Premier Book for you to read
From the start, it is not so hard, and easy to warm up with. I have not reached the further part. In general, this book is fine, but something it is not introduced to the detail. If you are interested in some great examples, funny problems it may disoppointed you. But if you are looking for learning some new concept and you are totally a rookie to Stochasic Processing, this just is the right one for you.
4 out of 5 stars
by brommhochariOct 08, 2008
For more advanced users
This book is for more advanced users. The book assumes that you already are somewhat familiar with the subject area and doesn't explain much of those basic ideas.
1 out of 5 stars
by moXq5bL2RLO@Del...Oct 09, 2006
I did not receive my order after two months.......
I paid but I did not receive any thing after almost two months. I am really down because this is the book that I really need in this semester. I still did not receive my money back. I am not sure what will be happen to the money which I paid.
4 out of 5 stars
by brdalqushJan 28, 2011
Probability and Random Processes
this book is a very good source of information and examples about the probability theory for those who are studying engineering.
5 out of 5 stars
by NayaqRhGQZK@Del...Mar 07, 2007
Recommendation
I'd recommend other people that are interested in buying this textbook, to buy along with it the Schaum's Outlines of probability and random processes with applications to signal processing where actually shows you solved problems to help the student undestand the materials better.

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Probability and Random Processes with Applications to Signal Processing by John W. Woods and Henry Stark (2001, Hardcover)

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I did not receive my order after two months.......

Probability and Random Processes

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