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Modern Spectrum Analysis of Time Series Fast Algorithms and Error Control
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Modern Spectrum Analysis of Time Series Fast Algorithms and Error Control Techniques Hardcover - 1995

by Prabhakar S. Naidu


From the publisher

Spectrum analysis can be considered as a topic in statistics as well as a topic in digital signal processing (DSP). This book takes a middle course by emphasizing the time series models and their impact on spectrum analysis.
The text begins with elements of probability theory and goes on to introduce the theory of stationary stochastic processes. The depth of coverage is extensive. Many topics of concern to spectral characterization of Gaussian and non-Gaussian time series, scalar and vector time series are covered. A section is devoted to the emerging areas of non-stationary and cyclostationary time series.
The book is organized more as a textbook than a reference book. Each chapter includes many examples to illustrate the concepts described. Several exercises are included at the end of each chapter. The level is appropriate for graduate and research students.

First line

An observed signal, presumed to be sampled or intrinsically discrete (e.g., rainfall time series), is treated as a stochastic process which, if Gaussian, may be characterized within the framework of second order statistics, namely, covariance function or spectrum density function.

Details

  • Title Modern Spectrum Analysis of Time Series Fast Algorithms and Error Control Techniques
  • Author Prabhakar S. Naidu
  • Binding Hardcover
  • Edition 2nd
  • Pages 416
  • Language ENG
  • Publisher CRC, Boca Raton, FL.
  • Date October 25, 1995
  • ISBN 9780849324642
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Modern Spectrum Analysis of Time Series
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Modern Spectrum Analysis of Time Series

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MODERN SPECTRUM ANALYSIS OF TIME SERIES - FAST ALGORITHMS AND ERROR CONTROL TECHNIQUES
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Boca Raton, FL.: CRC Press, 1996. Comprehensive text emphasizes the time series models and their impact on spectrum analysis. Includes detailed coverage of the elements of probability theory; theory of stationary stochastic processes; spectral characterization of Gaussian and non-Gaussian time series; scalar and vector time series; non-stationary and cyclostationary time series; spectrum estimation; etc. 399 pgs. Illustrated. . First Edition. Hard Cover. Fine. 4to - over 9¾" - 12" tall.
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Modern Spectrum Analysis of Time Series - Fast Algorithms and Error Control Techniques
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Modern Spectrum Analysis of Time Series - Fast Algorithms and Error Control Techniques

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Modern Spectrum Analysis of Time Series - Fast Algorithms and Error Control Techniques

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