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

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CRC Press, Oct 25, 1995 - Mathematics - 416 pages
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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.
 

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Contents

Chapter
1
Chapter Four
19
Chapter
71
Chapter Three
161
HighResolution Methods
241
Chapter Five
337
Index
393
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