An Introduction to Statistical Signal Processing

Introduces the tools and techniques of statistical signal processing. Includes overview of basic probability, random objects, expectation, and second-order moment theory, with examples of random process models and their basic uses and properties.

**Tag(s):**
Signal Processing

**Publication date**: 04 Jan 2005

**ISBN-10**:
0521838606

**ISBN-13**:
9780521838603

**Paperback**:
475 pages

**Views**: 20,418

An Introduction to Statistical Signal Processing

Introduces the tools and techniques of statistical signal processing. Includes overview of basic probability, random objects, expectation, and second-order moment theory, with examples of random process models and their basic uses and properties.

Terms and Conditions:

Book Excerpts:

This book was began as a second edition to Random Processes: A Mathematical Approach for Engineers. The basic goal remains unchanged - to introduce the fundamental ideas and mechanics of random processes to engineers in a way that accurately reflects the underlying mathematics, but does not require an extensive mathematical background and does not belabor detailed general proofs when simple cases suffice to get the basic ideas across.

In the years passed, the emphasis of this book has shifted increasingly towards the tools and techniques of statistical signal processing. At every stage on this book, 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 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.

Even though a student completing this book will not be able to follow the details in the literature of many proofs of results involving random processes, the basic results and their development and implications should be accessible, and the most common examples of random processes and classes of random processes should be familiar.

Intended Audience:

The prerequisites for this book are elementary set theory, elementary probability, and some familiarity with linear systems theory (Fourier analysis, convolution, discrete and continuous time linear filters, and transfer functions).

Robert M. Gray wrote:The material is copyrighted by Cambridge University Press, but is freely available as a pdf file to any individuals who wish to use it provided only that the contents of the entire text remain intact and together.

Book Excerpts:

This book was began as a second edition to Random Processes: A Mathematical Approach for Engineers. The basic goal remains unchanged - to introduce the fundamental ideas and mechanics of random processes to engineers in a way that accurately reflects the underlying mathematics, but does not require an extensive mathematical background and does not belabor detailed general proofs when simple cases suffice to get the basic ideas across.

In the years passed, the emphasis of this book has shifted increasingly towards the tools and techniques of statistical signal processing. At every stage on this book, 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 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.

Even though a student completing this book will not be able to follow the details in the literature of many proofs of results involving random processes, the basic results and their development and implications should be accessible, and the most common examples of random processes and classes of random processes should be familiar.

Intended Audience:

The prerequisites for this book are elementary set theory, elementary probability, and some familiarity with linear systems theory (Fourier analysis, convolution, discrete and continuous time linear filters, and transfer functions).

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