Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Download Data Adaptive Spectral Analysis Methods full books in PDF, epub, and Kindle. Read online Data Adaptive Spectral Analysis Methods ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author : Richard T. Lacoss
Publisher :
ISBN 13 :
Total Pages : 15 pages
Book Rating : 4.:/5 (656 download)
Download or read book Data Adaptive Spectral Analysis Methods written by Richard T. Lacoss and published by . This book was released on 1971 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : John William Moffett
Publisher :
ISBN 13 :
Total Pages : 140 pages
Book Rating : 4.:/5 (241 download)
Download or read book The Effects of Measurement Errors on Data Adaptive Spectral Analysis Methods written by John William Moffett and published by . This book was released on 1974 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Nicholas C. V. Pollock
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (131 download)
Download or read book Data Adaptive Spectral Analysis written by Nicholas C. V. Pollock and published by . This book was released on 1978 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Steve F. Russell
Publisher : Steve F. Russell
ISBN 13 :
Total Pages : 500 pages
Book Rating : 4./5 ( download)
Download or read book Spectral analysis methods for noisy sampled-data systems written by Steve F. Russell and published by Steve F. Russell. This book was released on 1978-08-15 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation covers both the theory and practice of estimating the spectrum of signals in noise using digital data. The theory of describing some of the signal processing concepts for digital data are given and various spectral estimation methods are given. The theory of MEM is described in detail using approaches from estimation theory, communication theory, and statistics. The work was intended to give researchers the theory and practice of practical means of spectral estimation using communications or scientific data. The Maximum Entropy Method by John Parker Burg is explained from what was known in 1974-75. KEY WORDS: Calculus-of-Variations, Data Systems, Noise , Spectrum Analysis, Time Series Analysis, Autocorrelation, Computer Programs, Data Windowing, Ergodic Process, Maximum Entropy Method (MEM, Fourier Transformation, Optimum Order of Estimation, Sampling, Spectral Resolution, Statistical Significance Test, Systems Analysis, Wiener-Khinchine Theorem. From The Smithsonian/NASA Astrophysics Data System -- The practical aspects of spectral analysis are contrasted with the mathematical theory. Treatment is limited to ergodic processes and emphasizes data window and noise effects. The Discrete Fourier Transform (DFT) and Maximum Entropy Method (MEM) are covered extensively both in theory and application with FORTRAN programs and many examples being provided. Several of the chapters are tutorial and discuss the important topics of sampling theory and system analysis. Topics on MEM include a complete calculus-of-variations solution, relationship between MEM and the Wiener-Khinchine relations, spectral resolution, and choosing the optimum order of the estimation. DFT leakage effects are modeled. A statistical significance test was developed to determine the realness of a spectral component. Keywords: Data Systems, Noise (Sound), Spectrum Analysis, Time Series Analysis, Autocorrelation, Computer Programs, Ergodic Process, Fourier Transformation, Sampling, Systems Analysis [less]
Author : Yanwei Wang
Publisher : Springer Nature
ISBN 13 : 3031025253
Total Pages : 99 pages
Book Rating : 4.0/5 (31 download)
Download or read book Spectral Analysis of Signals written by Yanwei Wang and published by Springer Nature. This book was released on 2022-05-31 with total page 99 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.
Author : Yanwei Wang
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1598290002
Total Pages : 108 pages
Book Rating : 4.5/5 (982 download)
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.
Author : E. R. Kanasewich
Publisher : University of Alberta
ISBN 13 : 9780888640741
Total Pages : 500 pages
Book Rating : 4.6/5 (47 download)
Download or read book Time Sequence Analysis in Geophysics: Third Edition written by E. R. Kanasewich and published by University of Alberta. This book was released on 1981 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time sequence analysis is the study of relations between a sequence of data points or sequence of signals in order to determine the physical properties of the earth. Providing an up-to-date treatment on time series and time sequence, this book is intended for senior or graduate students in seismology, geomagnetism and exploratory geophysics.
Author : Charles Lynn Whittington
Publisher :
ISBN 13 :
Total Pages : 114 pages
Book Rating : 4.:/5 (346 download)
Download or read book A system's approach to implementing time adaptive spectral analysis written by Charles Lynn Whittington and published by . This book was released on 1974 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : S. Lawrence Marple, Jr.
Publisher : Courier Dover Publications
ISBN 13 : 0486838862
Total Pages : 435 pages
Book Rating : 4.4/5 (868 download)
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: Designed to offer a broad perspective on spectral estimations techniques and their implementation, this text provides theoretical background and review material in linear systems, Fourier transforms, matrix algebra, random processes, and statistics. 1987 edition.
Author : Burkhard Buttkus
Publisher : Springer Science & Business Media
ISBN 13 : 364257016X
Total Pages : 665 pages
Book Rating : 4.6/5 (425 download)
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 2012-12-06 with total page 665 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.
Author : Francis Castanié
Publisher : John Wiley & Sons
ISBN 13 : 1118601831
Total Pages : 297 pages
Book Rating : 4.1/5 (186 download)
Download or read book Digital Spectral Analysis written by Francis Castanié and published by John Wiley & Sons. This book was released on 2013-02-04 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature. The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models. An entire chapter is devoted to the non-parametric methods most widely used in industry. High resolution methods are detailed in a further four chapters: spectral analysis by stationary time series modeling, minimum variance, and subspace-based estimators. Finally, advanced concepts are the core of the last four chapters: spectral analysis of non-stationary random signals, space time adaptive processing: irregularly sampled data processing, particle filtering and tracking of varying sinusoids. Suitable for students, engineers working in industry, and academics at any level, this book provides a rare complete overview of the spectral analysis domain.
Author : Ravindran Kannan
Publisher : Now Publishers Inc
ISBN 13 : 1601982747
Total Pages : 153 pages
Book Rating : 4.6/5 (19 download)
Download or read book Spectral Algorithms written by Ravindran Kannan and published by Now Publishers Inc. This book was released on 2009 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral methods refer to the use of eigenvalues, eigenvectors, singular values and singular vectors. They are widely used in Engineering, Applied Mathematics and Statistics. More recently, spectral methods have found numerous applications in Computer Science to "discrete" as well as "continuous" problems. Spectral Algorithms describes modern applications of spectral methods, and novel algorithms for estimating spectral parameters. The first part of the book presents applications of spectral methods to problems from a variety of topics including combinatorial optimization, learning and clustering. The second part of the book is motivated by efficiency considerations. A feature of many modern applications is the massive amount of input data. While sophisticated algorithms for matrix computations have been developed over a century, a more recent development is algorithms based on "sampling on the fly" from massive matrices. Good estimates of singular values and low rank approximations of the whole matrix can be provably derived from a sample. The main emphasis in the second part of the book is to present these sampling methods with rigorous error bounds. It also presents recent extensions of spectral methods from matrices to tensors and their applications to some combinatorial optimization problems.
Author : G. Larry Bretthorst
Publisher : Springer Science & Business Media
ISBN 13 : 146849399X
Total Pages : 210 pages
Book Rating : 4.4/5 (684 download)
Download or read book Bayesian Spectrum Analysis and Parameter Estimation written by G. Larry Bretthorst and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work is essentially an extensive revision of my Ph.D. dissertation, [1J. It 1S primarily a research document on the application of probability theory to the parameter estimation problem. The people who will be interested in this material are physicists, economists, and engineers who have to deal with data on a daily basis; consequently, we have included a great deal of introductory and tutorial material. Any person with the equivalent of the mathematics background required for the graduate level study of physics should be able to follow the material contained in this book, though not without eIfort. From the time the dissertation was written until now (approximately one year) our understanding of the parameter estimation problem has changed extensively. We have tried to incorporate what we have learned into this book. I am indebted to a number of people who have aided me in preparing this docu ment: Dr. C. Ray Smith, Steve Finney, Juana Sunchez, Matthew Self, and Dr. Pat Gibbons who acted as readers and editors. In addition, I must extend my deepest thanks to Dr. Joseph Ackerman for his support during the time this manuscript was being prepared.
Author : Richard E. Thomson
Publisher : Elsevier
ISBN 13 : 0080477003
Total Pages : 654 pages
Book Rating : 4.0/5 (84 download)
Download or read book Data Analysis Methods in Physical Oceanography written by Richard E. Thomson and published by Elsevier. This book was released on 2001-04-03 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analysis Methods in Physical Oceanography is a practical referenceguide to established and modern data analysis techniques in earth and oceansciences. This second and revised edition is even more comprehensive with numerous updates, and an additional appendix on 'Convolution and Fourier transforms'. Intended for both students and established scientists, the fivemajor chapters of the book cover data acquisition and recording, dataprocessing and presentation, statistical methods and error handling,analysis of spatial data fields, and time series analysis methods. Chapter 5on time series analysis is a book in itself, spanning a wide diversity oftopics from stochastic processes and stationarity, coherence functions,Fourier analysis, tidal harmonic analysis, spectral and cross-spectralanalysis, wavelet and other related methods for processing nonstationarydata series, digital filters, and fractals. The seven appendices includeunit conversions, approximation methods and nondimensional numbers used ingeophysical fluid dynamics, presentations on convolution, statisticalterminology, and distribution functions, and a number of importantstatistical tables. Twenty pages are devoted to references. Featuring:• An in-depth presentation of modern techniques for the analysis of temporal and spatial data sets collected in oceanography, geophysics, and other disciplines in earth and ocean sciences.• A detailed overview of oceanographic instrumentation and sensors - old and new - used to collect oceanographic data.• 7 appendices especially applicable to earth and ocean sciences ranging from conversion of units, through statistical tables, to terminology and non-dimensional parameters. In praise of the first edition: "(...)This is a very practical guide to the various statistical analysis methods used for obtaining information from geophysical data, with particular reference to oceanography(...)The book provides both a text for advanced students of the geophysical sciences and a useful reference volume for researchers." Aslib Book Guide Vol 63, No. 9, 1998 "(...)This is an excellent book that I recommend highly and will definitely use for my own research and teaching." EOS Transactions, D.A. Jay, 1999 "(...)In summary, this book is the most comprehensive and practical source of information on data analysis methods available to the physical oceanographer. The reader gets the benefit of extremely broad coverage and an excellent set of examples drawn from geographical observations." Oceanography, Vol. 12, No. 3, A. Plueddemann, 1999 "(...)Data Analysis Methods in Physical Oceanography is highly recommended for a wide range of readers, from the relative novice to the experienced researcher. It would be appropriate for academic and special libraries." E-Streams, Vol. 2, No. 8, P. Mofjelf, August 1999
Author : Silvia Maria Alessio
Publisher : Springer
ISBN 13 : 3319254685
Total Pages : 909 pages
Book Rating : 4.3/5 (192 download)
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.
Author : B.M. Båth
Publisher : Elsevier
ISBN 13 : 0444599983
Total Pages : 580 pages
Book Rating : 4.4/5 (445 download)
Download or read book Spectral Analysis in Geophysics written by B.M. Båth and published by Elsevier. This book was released on 2012-12-02 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral Analysis in Geophysics
Author : M. Kaveh
Publisher :
ISBN 13 :
Total Pages : 91 pages
Book Rating : 4.:/5 (227 download)
Download or read book Adaptive High Resolution Spectral Analysis with Noisy Data written by M. Kaveh and published by . This book was released on 1980 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report summarizes the results of research during the past two years, in understanding the resolution of the autoregressive (AR) spectral estimators and developing and evaluating computationally efficient autoregressive-moving average (ARMA) spectral estimators. The loss in the resolution of the AR spectral estimator in the presence of noise is related to the appearance of zeros in the z-plane. A parallel resonator model is developed to relate the loss in resolution (bandwidth expansion) to the signal-to-noise ratio and parameters of the noiseless signal model. A new technique for the identification of the order of an AR model was derived that shows substantial stability compared to the popular Akaike Information Criterion method. Order determination was emphasized, since increase in the order of the AR spectral estimator, to account for the presence of noise, is naturally accompanied by larger variance of the estimates and appearance of spurious peaks. Several sub-optimum (non-maximum-likelihood) ARMA spectral estimators were also developed. These methods are computationally efficient, but statistically not very stable for small data records. An evaluation of the statistical properties of the different sub-optimum ARMA techniques led to the evaluation of asymptotic bounds on the variances of the estimates of the parameters or the poles and zeros of the model through the evaluation of Fisher's information matrix.
