Fundamentals of Statistical Signal Processing, Volume 1: Estimation Theory

Fundamentals of Statistical Signal Processing, Volume 1: Estimation Theory PDF Author: Kay
Publisher: Pearson Education India
ISBN: 9788131728994
Category :
Languages : en
Pages : 612

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Book Description


Fundamentals of Statistical Signal Processing

Fundamentals of Statistical Signal Processing PDF Author: Steven M. Kay
Publisher: Pearson Education
ISBN: 013280803X
Category : Technology & Engineering
Languages : en
Pages : 496

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Book Description
"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for obtaining an optimal estimator and analyzing its performance. Author Steven M. Kay discusses classical estimation followed by Bayesian estimation, and illustrates the theory with numerous pedagogical and real-world examples."--Cover, volume 1.

Fundamentals of Statistical Signal Processing: Detection theory

Fundamentals of Statistical Signal Processing: Detection theory PDF Author: Steven M. Kay
Publisher: Pearson
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 584

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Book Description
V.2 Detection theory -- V.1 Estimation theory.

Fundamentals of Statistical Signal Processing

Fundamentals of Statistical Signal Processing PDF Author: Steven M. Kay
Publisher: Prentice Hall
ISBN: 9780130422682
Category : Estimation theory
Languages : en
Pages : 595

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Book Description


Fundamentals of Statistical Signal Processing

Fundamentals of Statistical Signal Processing PDF Author: Steven M. Kay
Publisher:
ISBN: 9780134878409
Category : Estimation theory
Languages : en
Pages : 0

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Book Description
"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for obtaining an optimal estimator and analyzing its performance. Author Steven M. Kay discusses classical estimation followed by Bayesian estimation, and illustrates the theory with numerous pedagogical and real-world examples."--Cover, volume 1.

Statistical Signal Processing

Statistical Signal Processing PDF Author: Louis L. Scharf
Publisher: Prentice Hall
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 552

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Book Description
This book embraces the many mathematical procedures that engineers and statisticians use to draw inference from imperfect or incomplete measurements. This book presents the fundamental ideas in statistical signal processing along four distinct lines: mathematical and statistical preliminaries; decision theory; estimation theory; and time series analysis.

Foundations of Signal Processing

Foundations of Signal Processing PDF Author: Martin Vetterli
Publisher: Cambridge University Press
ISBN: 1139916572
Category : Technology & Engineering
Languages : en
Pages : 745

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Book Description
This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications. Students are introduced to the powerful foundations of modern signal processing, including the basic geometry of Hilbert space, the mathematics of Fourier transforms, and essentials of sampling, interpolation, approximation and compression The authors discuss real-world issues and hurdles to using these tools, and ways of adapting them to overcome problems of finiteness and localization, the limitations of uncertainty, and computational costs. It includes over 160 homework problems and over 220 worked examples, specifically designed to test and expand students' understanding of the fundamentals of signal processing, and is accompanied by extensive online materials designed to aid learning, including Mathematica® resources and interactive demonstrations.

An Introduction to Statistical Signal Processing

An Introduction to Statistical Signal Processing PDF Author: Robert M. Gray
Publisher: Cambridge University Press
ISBN: 1139456288
Category : Technology & Engineering
Languages : en
Pages : 479

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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 using a range of carefully chosen examples. 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. Hundreds of homework problems are included and the book is ideal for graduate students of electrical engineering and applied mathematics. It is also a useful reference for researchers in signal processing and communications.

Modern Spectral Estimation

Modern Spectral Estimation PDF Author: Steven M. Kay
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 574

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Book Description


An Introduction to Signal Detection and Estimation

An Introduction to Signal Detection and Estimation PDF Author: H. Vincent Poor
Publisher: Springer Science & Business Media
ISBN: 1475738633
Category : Technology & Engineering
Languages : en
Pages : 558

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Book Description
The purpose of this book is to introduce the reader to the basic theory of signal detection and estimation. It is assumed that the reader has a working knowledge of applied probabil ity and random processes such as that taught in a typical first-semester graduate engineering course on these subjects. This material is covered, for example, in the book by Wong (1983) in this series. More advanced concepts in these areas are introduced where needed, primarily in Chapters VI and VII, where continuous-time problems are treated. This book is adapted from a one-semester, second-tier graduate course taught at the University of Illinois. However, this material can also be used for a shorter or first-tier course by restricting coverage to Chapters I through V, which for the most part can be read with a background of only the basics of applied probability, including random vectors and conditional expectations. Sufficient background for the latter option is given for exam pIe in the book by Thomas (1986), also in this series.