Introduction to Spectral Analysis
Introduction to Spectral Analysis

Author: Petre Stoica

Publisher: Pearson Education

Published: 1997

Total Pages: 358

ISBN-13:

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This book presents an introduction to spectral analysis that is designed for either course use or self-study. Clear and concise in approach, it develops a firm understanding of tools and techniques as well as a solid background for performing research. Topics covered include nonparametric spectrum analysis (both periodogram-based approaches and filter- bank approaches), parametric spectral analysis using rational spectral models (AR, MA, and ARMA models), parametric method for line spectra, and spatial (array) signal processing. Analytical and Matlab-based computer exercises are included to develop both analytical skills and hands-on experience.

Modern Spectrum Analysis of Time Series
Modern Spectrum Analysis of Time Series

Author: Prabhakar S. Naidu

Publisher: CRC Press

Published: 1995-10-25

Total Pages: 424

ISBN-13: 9780849324642

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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.

NMR-Spectroscopy: Modern Spectral Analysis
NMR-Spectroscopy: Modern Spectral Analysis

Author: Ursula Weber

Publisher: John Wiley & Sons

Published: 2008-11-21

Total Pages: 409

ISBN-13: 3527612327

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The state-of-the-art in NMR spectral analysis. This interactive tutorial provides readers with a comprehensive range of software tools and techniques, as well as the necessary theoretical knowledge required to analyze their spectra and obtain the correct NMR parameters. Modern Spectral Analysis provides expert guidance, by presenting efficient strategies to extract NMR parameters from measured spectra. A database of selected spectra and modern, powerful WIN-NMR software designed by Bruker are provided on the enclosed CD-ROM. The programs provided are 1 D WIN-NMR, WIN-DAISY, WIN-DR and WIN-DYNAMICS, and direct data exchange between all these programs is possible. Readers are shown how they can obtain maximum structural information from their 1 D NMR spectra with time-saving computer assistance. Practical problems that can occur and their solutions are discussed at length using clear, easy-to-follow examples. Both homo- and heteronuclear and first- and second-order spin systems are demonstrated. Moreover, relaxation analysis, nuclear Overhauser effects and magnetic site exchange are all covered in this hands-on guide to NMR spectral analysis.

Spectral Analysis of Signals
Spectral Analysis of Signals

Author: Yanwei Wang

Publisher: Morgan & Claypool Publishers

Published: 2005

Total Pages: 108

ISBN-13: 1598290002

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Spectral estimation is important in many fields including astronomy, meteorology, seismology, communications, economics, speech analysis, medical imaging, radar, sonar, and underwater acoustics. Most existing spectral estimation algorithms are devised for uniformly sampled complete-data sequences. However, the spectral estimation for data sequences with missing samples is also important in many applications ranging from astronomical time series analysis to synthetic aperture radar imaging with angular diversity. For spectral estimation in the missing-data case, the challenge is how to extend the existing spectral estimation techniques to deal with these missing-data samples. Recently, nonparametric adaptive filtering based techniques have been developed successfully for various missing-data problems. Collectively, these algorithms provide a comprehensive toolset for the missing-data problem based exclusively on the nonparametric adaptive filter-bank approaches, which are robust and accurate, and can provide high resolution and low sidelobes. In this book, we present these algorithms for both one-dimensional and two-dimensional spectral estimation problems.

Spectral Analysis for Physical Applications
Spectral Analysis for Physical Applications

Author: Donald B. Percival

Publisher: Cambridge University Press

Published: 1993-06-03

Total Pages: 616

ISBN-13: 9780521435413

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This book is an up-to-date introduction to univariate spectral analysis at the graduate level, which reflects a new scientific awareness of spectral complexity, as well as the widespread use of spectral analysis on digital computers with considerable computational power. The text provides theoretical and computational guidance on the available techniques, emphasizing those that work in practice. Spectral analysis finds extensive application in the analysis of data arising in many of the physical sciences, ranging from electrical engineering and physics to geophysics and oceanography. A valuable feature of the text is that many examples are given showing the application of spectral analysis to real data sets. Special emphasis is placed on the multitaper technique, because of its practical success in handling spectra with intricate structure, and its power to handle data with or without spectral lines. The text contains a large number of exercises, together with an extensive bibliography.