This volume describes the essential tools and techniques of statistical signal processing. At every stage, theoretical ideas are linked to specific applications in communications and signal processing. The book begins with an overview of basic probability, random objects, expectation, and second-order moment theory, followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the text.
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"One of the book's strengths is its thematic focus, guiding the reader on a straight road to mean squared calculus. The authors are careful in not assuming prior knowledge of probability theory or even measure theory, and the text connects readily to undergraduate courses on elementary probability and linear systems. The writing itself is carved in a sequential and elaborate style following the credo of linear development of material. Emphasizing intuitive arguments, the text provides helpful discussions of notions and basic concepts. A wealth of problem questions are proposed." - Journal of the American Statistical Association.
Book Description
This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book.
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Inside This Book
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First Sentence:
A random or stochastic process is a mathematical model for a phenomenon that evolves in time in an unpredictable manner from the viewpoint of the observer. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
iid random process, geometric pmf, product pmf, binary random process, conditional pmf, random telegraph wave, joint pmf, iid process, discrete time random process, input random process, marginal pmf, uniform pmf, resulting mean squared error, convergence with probability one, square calculus, continuous time random process, new random process, single coin flip, continuous alphabet, binomial pmf, multidimensional pdf, independent increment processes, exponential modulation, original probability space, autoregressive filter New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
A random or stochastic process is a mathematical model for a phenomenon that evolves in time in an unpredictable manner from the viewpoint of the observer. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
iid random process, geometric pmf, product pmf, binary random process, conditional pmf, random telegraph wave, joint pmf, iid process, discrete time random process, input random process, marginal pmf, uniform pmf, resulting mean squared error, convergence with probability one, square calculus, continuous time random process, new random process, single coin flip, continuous alphabet, binomial pmf, multidimensional pdf, independent increment processes, exponential modulation, original probability space, autoregressive filter New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 46
books:
See all 46 books this book cites
3
books
cite this book:
- Random Processes. (Graduate Texts in Mathematics) by M. Rosenblatt in Back Matter (1), and Back Matter (2)
- Fourier Transforms: An Introduction for Engineers (The Springer International Series in Engineering and Computer Science) by Robert M. Gray in Back Matter (1), and Back Matter (2)
- An Introduction to the Theory of Stationary Random Functions (Dover Phoenix Editions) by A. M. Yaglom in Back Matter
- Stochastic Integrals (Ams Chelsea Publishing) by Henry P. McKean in Back Matter
- Theory of Probability by Boris V. Gnedenko in Back Matter
See all 46 books this book cites
- Signal Detection and Estimation [With CDROM] (Artech House Radar Library) by Mourad Barkat on page 221
- Probability and Random Processes for Electrical and Computer Engineers by John A. Gubner in Back Matter
- Toeplitz and Circulant Matrices: A review (Foundations and Trends in Communications and Information The) by Robert M. Gray in Back Matter
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