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An Introduction To Spectral Analysis
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Book Synopsis Spectral Analysis of Signals by : Yanwei Wang
Download or read book Spectral Analysis of Signals written by Yanwei Wang and published by Morgan & Claypool Publishers. This book was released on 2005 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Introduction to Spectral Analysis by : Petre Stoica
Download or read book Introduction to Spectral Analysis written by Petre Stoica and published by Pearson Education. This book was released on 1997 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Spectral Analysis for Physical Applications by : Donald B. Percival
Download or read book Spectral Analysis for Physical Applications written by Donald B. Percival and published by Cambridge University Press. This book was released on 1993-06-03 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis The Spectral Analysis of Time Series by : L. H. Koopmans
Download or read book The Spectral Analysis of Time Series written by L. H. Koopmans and published by Academic Press. This book was released on 2014-05-12 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Spectral Analysis of Time Series describes the techniques and theory of the frequency domain analysis of time series. The book discusses the physical processes and the basic features of models of time series. The central feature of all models is the existence of a spectrum by which the time series is decomposed into a linear combination of sines and cosines. The investigator can used Fourier decompositions or other kinds of spectrals in time series analysis. The text explains the Wiener theory of spectral analysis, the spectral representation for weakly stationary stochastic processes, and the real spectral representation. The book also discusses sampling, aliasing, discrete-time models, linear filters that have general properties with applications to continuous-time processes, and the applications of multivariate spectral models. The text describes finite parameter models, the distribution theory of spectral estimates with applications to statistical inference, as well as sampling properties of spectral estimates, experimental design, and spectral computations. The book is intended either as a textbook or for individual reading for one-semester or two-quarter course for students of time series analysis users. It is also suitable for mathematicians or professors of calculus, statistics, and advanced mathematics.
Book Synopsis Spectral Analysis and Its Applications by : Gwilym M. Jenkins
Download or read book Spectral Analysis and Its Applications written by Gwilym M. Jenkins and published by Emerson Adams PressInc. This book was released on 1968 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Introduction to Random Vibrations, Spectral & Wavelet Analysis by : D. E. Newland
Download or read book An Introduction to Random Vibrations, Spectral & Wavelet Analysis written by D. E. Newland and published by Courier Corporation. This book was released on 2012-04-03 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic describes and illustrates basic theory, with a detailed explanation of discrete wavelet transforms. Suitable for upper-level undergraduates, it is also a practical resource for professionals.
Book Synopsis Spectral Analysis of Large Dimensional Random Matrices by : Zhidong Bai
Download or read book Spectral Analysis of Large Dimensional Random Matrices written by Zhidong Bai and published by Springer Science & Business Media. This book was released on 2009-12-10 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of the book is to introduce basic concepts, main results, and widely applied mathematical tools in the spectral analysis of large dimensional random matrices. The core of the book focuses on results established under moment conditions on random variables using probabilistic methods, and is thus easily applicable to statistics and other areas of science. The book introduces fundamental results, most of them investigated by the authors, such as the semicircular law of Wigner matrices, the Marcenko-Pastur law, the limiting spectral distribution of the multivariate F matrix, limits of extreme eigenvalues, spectrum separation theorems, convergence rates of empirical distributions, central limit theorems of linear spectral statistics, and the partial solution of the famous circular law. While deriving the main results, the book simultaneously emphasizes the ideas and methodologies of the fundamental mathematical tools, among them being: truncation techniques, matrix identities, moment convergence theorems, and the Stieltjes transform. Its treatment is especially fitting to the needs of mathematics and statistics graduate students and beginning researchers, having a basic knowledge of matrix theory and an understanding of probability theory at the graduate level, who desire to learn the concepts and tools in solving problems in this area. It can also serve as a detailed handbook on results of large dimensional random matrices for practical users. This second edition includes two additional chapters, one on the authors' results on the limiting behavior of eigenvectors of sample covariance matrices, another on applications to wireless communications and finance. While attempting to bring this edition up-to-date on recent work, it also provides summaries of other areas which are typically considered part of the general field of random matrix theory.
Book Synopsis Mathematics and the Aesthetic by : Nathalie Sinclair
Download or read book Mathematics and the Aesthetic written by Nathalie Sinclair and published by Springer Science & Business Media. This book was released on 2007-12-28 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of essays explores the ancient affinity between the mathematical and the aesthetic, focusing on fundamental connections between these two modes of reasoning and communicating. From historical, philosophical and psychological perspectives, with particular attention to certain mathematical areas such as geometry and analysis, the authors examine ways in which the aesthetic is ever-present in mathematical thinking and contributes to the growth and value of mathematical knowledge.
Book Synopsis Introduction to Spectral Theory in Hilbert Space by : Gilbert Helmberg
Download or read book Introduction to Spectral Theory in Hilbert Space written by Gilbert Helmberg and published by Elsevier. This book was released on 2014-11-28 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: North-Holland Series in Applied Mathematics and Mechanics, Volume 6: Introduction to Spectral Theory in Hilbert Space focuses on the mechanics, principles, and approaches involved in spectral theory in Hilbert space. The publication first elaborates on the concept and specific geometry of Hilbert space and bounded linear operators. Discussions focus on projection and adjoint operators, bilinear forms, bounded linear mappings, isomorphisms, orthogonal subspaces, base, subspaces, finite dimensional Euclidean space, and normed linear spaces. The text then takes a look at the general theory of linear operators and spectral analysis of compact linear operators, including spectral decomposition of a compact selfadjoint operator, weakly convergent sequences, spectrum of a compact linear operator, and eigenvalues of a linear operator. The manuscript ponders on the spectral analysis of bounded linear operators and unbounded selfadjoint operators. Topics include spectral decomposition of an unbounded selfadjoint operator and bounded normal operator, functions of a unitary operator, step functions of a bounded selfadjoint operator, polynomials in a bounded operator, and order relation for bounded selfadjoint operators. The publication is a valuable source of data for mathematicians and researchers interested in spectral theory in Hilbert space.
Book Synopsis Spectral Analysis and Filter Theory in Applied Geophysics by : Burkhard Buttkus
Download or read book Spectral Analysis and Filter Theory in Applied Geophysics written by Burkhard Buttkus and published by Springer Science & Business Media. This book was released on 2000-03-27 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: This state-of-the-art survey serves as a complete overview of the subject. Besides the principles and theoretical foundations, emphasis is laid on practical applicability -- describing not only classical methods, but also modern developments and their applications. Students, researchers and practitioners, especially in the fields of data registration, treatment and evaluation, will find this a wealth of information.
Book Synopsis Digital Signal Processing and Spectral Analysis for Scientists by : Silvia Maria Alessio
Download or read book Digital Signal Processing and Spectral Analysis for Scientists written by Silvia Maria Alessio and published by Springer. This book was released on 2015-12-09 with total page 909 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawbacks of the various methods and to highlight possible misuses. The book is rich in original ideas, visualized in new and illuminating ways, and is structured so that parts can be skipped without loss of continuity. Many examples are included, based on synthetic data and real measurements from the fields of physics, biology, medicine, macroeconomics etc., and a complete set of MATLAB exercises requiring no previous experience of programming is provided. Prior advanced mathematical skills are not needed in order to understand the contents: a good command of basic mathematical analysis is sufficient. Where more advanced mathematical tools are necessary, they are included in an Appendix and presented in an easy-to-follow way. With this book, digital signal processing leaves the domain of engineering to address the needs of scientists and scholars in traditionally less quantitative disciplines, now facing increasing amounts of data.
Book Synopsis Introduction to Spectral Theory by : P.D. Hislop
Download or read book Introduction to Spectral Theory written by P.D. Hislop and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: The intention of this book is to introduce students to active areas of research in mathematical physics in a rather direct way minimizing the use of abstract mathematics. The main features are geometric methods in spectral analysis, exponential decay of eigenfunctions, semi-classical analysis of bound state problems, and semi-classical analysis of resonance. A new geometric point of view along with new techniques are brought out in this book which have both been discovered within the past decade. This book is designed to be used as a textbook, unlike the competitors which are either too fundamental in their approach or are too abstract in nature to be considered as texts. The authors' text fills a gap in the marketplace.
Book Synopsis Spectral Analysis in Engineering by : Grant Hearn
Download or read book Spectral Analysis in Engineering written by Grant Hearn and published by Butterworth-Heinemann. This book was released on 1995-08-17 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text provides a thorough explanation of the underlying principles of spectral analysis and the full range of estimation techniques used in engineering. The applications of these techniques are demonstrated in numerous case studies, illustrating the approach required and the compromises to be made when solving real engineering problems. The principles outlined in these case studies are applicable over the full range of engineering disciplines and all the reader requires is an understanding of elementary calculus and basic statistics. The realistic approach and comprehensive nature of this text will provide undergraduate engineers and physicists of all disciplines with an invaluable introduction to the subject and the detailed case studies will interest the experienced professional. - No more than a knowledge of elementary calculus, and basic statistics and probability is needed - Accessible to undergraduates at any stage of their courses - Easy and clear to follow
Book Synopsis Digital Spectral Analysis by : S. Lawrence Marple, Jr.
Download or read book Digital Spectral Analysis written by S. Lawrence Marple, Jr. and published by Courier Dover Publications. This book was released on 2019-03-20 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital Spectral Analysis offers a broad perspective of spectral estimation techniques and their implementation. Coverage includes spectral estimation of discrete-time or discrete-space sequences derived by sampling continuous-time or continuous-space signals. The treatment emphasizes the behavior of each spectral estimator for short data records and provides over 40 techniques described and available as implemented MATLAB functions. In addition to summarizing classical spectral estimation, this text provides theoretical background and review material in linear systems, Fourier transforms, matrix algebra, random processes, and statistics. Topics include Prony's method, parametric methods, the minimum variance method, eigenanalysis-based estimators, multichannel methods, and two-dimensional methods. Suitable for advanced undergraduates and graduate students of electrical engineering — and for scientific use in the signal processing application community outside of universities — the treatment's prerequisites include some knowledge of discrete-time linear system and transform theory, introductory probability and statistics, and linear algebra. 1987 edition.
Book Synopsis Spectral Analysis of Time-series Data by : Rebecca M. Warner
Download or read book Spectral Analysis of Time-series Data written by Rebecca M. Warner and published by Guilford Press. This book was released on 1998-05-22 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough introduction to methods for detecting and describing cyclic patterns in time-series data. It is written both for researchers and students new to the area and for those who have already collected time-series data but wish to learn new ways of understanding and presenting them. Facilitating the interpretation of observations of behavior, physiology, mood, perceptual threshold, social indicator variables, and other responses, the book focuses on practical applications and requires much less mathematical background than most comparable texts. Using real data sets and currently available software (SPSS for Windows), the author employs extensive examples to clarify key concepts. Topics covered include research design issues, preliminary data screening, identification and description of cycles, summary of results across time series, and assessment of relations between time series. Also considered are theoretical questions, problems of interpretation, and potential sources of artifact.
Book Synopsis Spectral Analysis for Univariate Time Series by : Donald B. Percival
Download or read book Spectral Analysis for Univariate Time Series written by Donald B. Percival and published by Cambridge University Press. This book was released on 2020-03-19 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral analysis is widely used to interpret time series collected in diverse areas. This book covers the statistical theory behind spectral analysis and provides data analysts with the tools needed to transition theory into practice. Actual time series from oceanography, metrology, atmospheric science and other areas are used in running examples throughout, to allow clear comparison of how the various methods address questions of interest. All major nonparametric and parametric spectral analysis techniques are discussed, with emphasis on the multitaper method, both in its original formulation involving Slepian tapers and in a popular alternative using sinusoidal tapers. The authors take a unified approach to quantifying the bandwidth of different nonparametric spectral estimates. An extensive set of exercises allows readers to test their understanding of theory and practical analysis. The time series used as examples and R language code for recreating the analyses of the series are available from the book's website.
Book Synopsis Automatic Autocorrelation and Spectral Analysis by : Piet M. T. Broersen
Download or read book Automatic Autocorrelation and Spectral Analysis written by Piet M. T. Broersen and published by Springer Science & Business Media. This book was released on 2006-04-20 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral analysis requires subjective decisions which influence the final estimate and mean that different analysts can obtain different results from the same stationary stochastic observations. Statistical signal processing can overcome this difficulty, producing a unique solution for any set of observations but that is only acceptable if it is close to the best attainable accuracy for most types of stationary data. This book describes a method which fulfils the above near-optimal-solution criterion, taking advantage of greater computing power and robust algorithms to produce enough candidate models to be sure of providing a suitable candidate for given data.
