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| spectral analysis for physical applications: Spectral Analysis for Physical Applications Donald B. Percival, Andrew T. Walden, 1993-06-03 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. |
| spectral analysis for physical applications: Spectral Analysis For Physical Applications Multipaper And Conventional... D.B. Percival, |
| spectral analysis for physical applications: Engineering Applications of Correlation and Spectral Analysis Julius S. Bendat, Allan G. Piersol, 1980-05-13 Introduction and background; Probability functions and amplitude measures; Correlation and spectral density functions; Single input/single output relationships; System identification and response; Propagation path identification; Single input/multiple output problems; Multiple input/output relationships; Energy source identification; Procedures for solving multiple input/output problems; Statistical errors in measurements. |
| spectral analysis for physical applications: Spectral Methods Jie Shen, Tao Tang, Li-Lian Wang, 2011-08-25 Along with finite differences and finite elements, spectral methods are one of the three main methodologies for solving partial differential equations on computers. This book provides a detailed presentation of basic spectral algorithms, as well as a systematical presentation of basic convergence theory and error analysis for spectral methods. Readers of this book will be exposed to a unified framework for designing and analyzing spectral algorithms for a variety of problems, including in particular high-order differential equations and problems in unbounded domains. The book contains a large number of figures which are designed to illustrate various concepts stressed in the book. A set of basic matlab codes has been made available online to help the readers to develop their own spectral codes for their specific applications. |
| spectral analysis for physical applications: Spectral Analysis and Its Applications Gwilym M. Jenkins, Donald G. Watts, 1968 |
| spectral analysis for physical applications: Digital Spectral Analysis S. Lawrence Marple, Jr., 2019-03-20 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. |
| spectral analysis for physical applications: Spectral Analysis for Univariate Time Series Donald B. Percival, Andrew T. Walden, 2020-03-19 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. |
| spectral analysis for physical applications: Ten Physical Applications of Spectral Zeta Functions Emilio Elizalde, 2014-01-15 |
| spectral analysis for physical applications: Near-Infrared Spectroscopy Yukihiro Ozaki, Christian Huck, Satoru Tsuchikawa, Søren Balling Engelsen, 2020-11-13 This book provides knowledge of the basic theory, spectral analysis methods, chemometrics, instrumentation, and applications of near-infrared (NIR) spectroscopy—not as a handbook but rather as a sourcebook of NIR spectroscopy. Thus, some emphasis is placed on the description of basic knowledge that is important in learning and using NIR spectroscopy. The book also deals with applications for a variety of research fields that are very useful for a wide range of readers from graduate students to scientists and engineers in both academia and industry. For readers who are novices in NIR spectroscopy, this book provides a good introduction, and for those who already are familiar with the field it affords an excellent means of strengthening their knowledge about NIR spectroscopy and keeping abreast of recent developments. |
| spectral analysis for physical applications: Spectral Analysis of Relativistic Operators A. A. Balinsky, W. D. Evans, 2011 Over the last decade, there has been considerable interest and progress in determining the spectral properties of various operators that take relativistic effects into account, with important implications for mathematics and physics. Difficulties are encountered in many-particle problems due to the lack of semiboundedness of the Dirac operator, and this has led to the investigation of operators like those of Chandrasekhar-Herbst and Brown-Ravenhall, which are semibounded under appropriate circumstances.This book contains an up-to-date, comprehensive and self-contained analysis of the spectral properties of these operators, providing the tools for anyone working in this area. Another major feature is the work of the authors on zero modes, a topic which has important significance for the stability of matter and other physical problems. Up until now, these topics have been scattered throughout the literature, without a systematic and cohesive treatment. The book will report largely on the progress on these topics published since 1992. |
| spectral analysis for physical applications: Multi-scale Spectral Analysis in Hydrology Adarsh S, M Janga Reddy, 2021-03-01 Accurate prediction of hydrological variables is essential for efficient water resources planning and management. Proper understanding of the characteristics of the time series may help in improving the simulation and forecasting accuracy of hydrological variables. This book presents a detailed description and application of multiscale time-frequency characterization tool for the spectral analysis of hydrological time series. It presents spectral analysis methods for hydrological applications through a wide variety of illustrative case studies including Wavelet transforms, Hilbert Huang Transform and their extensions. |
| spectral analysis for physical applications: Data Analysis Methods in Physical Oceanography William J. Emery, Richard E. Thomson, 2001-04-03 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 |
| spectral analysis for physical applications: Spectral Methods And Their Applications Ben-yu Guo, 1998-05-05 This book presents the basic algorithms, the main theoretical results, and some applications of spectral methods. Particular attention is paid to the applications of spectral methods to nonlinear problems arising in fluid dynamics, quantum mechanics, weather prediction, heat conduction and other fields.The book consists of three parts. The first part deals with orthogonal approximations in Sobolev spaces and the stability and convergence of approximations for nonlinear problems, as the mathematical foundation of spectral methods. In the second part, various spectral methods are described, with some applications. It includes Fourier spectral method, Legendre spectral method, Chebyshev spectral method, spectral penalty method, spectral vanishing viscosity method, spectral approximation of isolated solutions, multi-dimensional spectral method, spectral method for high-order equations, spectral-domain decomposition method and spectral multigrid method. The third part is devoted to some recent developments of spectral methods, such as mixed spectral methods, combined spectral methods and spectral methods on the surface. |
| spectral analysis for physical applications: A Guide to Spectral Theory Christophe Cheverry, Nicolas Raymond, 2022-05-07 This textbook provides a graduate-level introduction to the spectral theory of linear operators on Banach and Hilbert spaces, guiding readers through key components of spectral theory and its applications in quantum physics. Based on their extensive teaching experience, the authors present topics in a progressive manner so that each chapter builds on the ones preceding. Researchers and students alike will also appreciate the exploration of more advanced applications and research perspectives presented near the end of the book. Beginning with a brief introduction to the relationship between spectral theory and quantum physics, the authors go on to explore unbounded operators, analyzing closed, adjoint, and self-adjoint operators. Next, the spectrum of a closed operator is defined and the fundamental properties of Fredholm operators are introduced. The authors then develop the Grushin method to execute the spectral analysis of compact operators. The chapters that follow are devoted to examining Hille-Yoshida and Stone theorems, the spectral analysis of self-adjoint operators, and trace-class and Hilbert-Schmidt operators. The final chapter opens the discussion to several selected applications. Throughout this textbook, detailed proofs are given, and the statements are illustrated by a number of well-chosen examples. At the end, an appendix about foundational functional analysis theorems is provided to help the uninitiated reader. A Guide to Spectral Theory: Applications and Exercises is intended for graduate students taking an introductory course in spectral theory or operator theory. A background in linear functional analysis and partial differential equations is assumed; basic knowledge of bounded linear operators is useful but not required. PhD students and researchers will also find this volume to be of interest, particularly the research directions provided in later chapters. |
| spectral analysis for physical applications: Functional Analysis, Spectral Theory, and Applications Manfred Einsiedler, Thomas Ward, 2017-11-21 This textbook provides a careful treatment of functional analysis and some of its applications in analysis, number theory, and ergodic theory. In addition to discussing core material in functional analysis, the authors cover more recent and advanced topics, including Weyl’s law for eigenfunctions of the Laplace operator, amenability and property (T), the measurable functional calculus, spectral theory for unbounded operators, and an account of Tao’s approach to the prime number theorem using Banach algebras. The book further contains numerous examples and exercises, making it suitable for both lecture courses and self-study. Functional Analysis, Spectral Theory, and Applications is aimed at postgraduate and advanced undergraduate students with some background in analysis and algebra, but will also appeal to everyone with an interest in seeing how functional analysis can be applied to other parts of mathematics. |
| spectral analysis for physical applications: Techniques and Applications of Hyperspectral Image Analysis Hans Grahn, Paul Geladi, 2007-09-27 Techniques and Applications of Hyperspectral Image Analysis gives an introduction to the field of image analysis using hyperspectral techniques, and includes definitions and instrument descriptions. Other imaging topics that are covered are segmentation, regression and classification. The book discusses how high quality images of large data files can be structured and archived. Imaging techniques also demand accurate calibration, and are covered in sections about multivariate calibration techniques. The book explains the most important instruments for hyperspectral imaging in more technical detail. A number of applications from medical and chemical imaging are presented and there is an emphasis on data analysis including modeling, data visualization, model testing and statistical interpretation. |
| spectral analysis for physical applications: Introduction to Spectral Analysis Petre Stoica, Randolph L. Moses, 1997 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. |
| spectral analysis for physical applications: Spectral Methods in Chemistry and Physics Bernard Shizgal, 2015-01-07 This book is a pedagogical presentation of the application of spectral and pseudospectral methods to kinetic theory and quantum mechanics. There are additional applications to astrophysics, engineering, biology and many other fields. The main objective of this book is to provide the basic concepts to enable the use of spectral and pseudospectral methods to solve problems in diverse fields of interest and to a wide audience. While spectral methods are generally based on Fourier Series or Chebychev polynomials, non-classical polynomials and associated quadratures are used for many of the applications presented in the book. Fourier series methods are summarized with a discussion of the resolution of the Gibbs phenomenon. Classical and non-classical quadratures are used for the evaluation of integrals in reaction dynamics including nuclear fusion, radial integrals in density functional theory, in elastic scattering theory and other applications. The subject matter includes the calculation of transport coefficients in gases and other gas dynamical problems based on spectral and pseudospectral solutions of the Boltzmann equation. Radiative transfer in astrophysics and atmospheric science, and applications to space physics are discussed. The relaxation of initial non-equilibrium distributions to equilibrium for several different systems is studied with the Boltzmann and Fokker-Planck equations. The eigenvalue spectra of the linear operators in the Boltzmann, Fokker-Planck and Schrödinger equations are studied with spectral and pseudospectral methods based on non-classical orthogonal polynomials. The numerical methods referred to as the Discrete Ordinate Method, Differential Quadrature, the Quadrature Discretization Method, the Discrete Variable Representation, the Lagrange Mesh Method, and others are discussed and compared. MATLAB codes are provided for most of the numerical results reported in the book - see Link under 'Additional Information' on the the right-hand column. |
| spectral analysis for physical applications: Chebyshev and Fourier Spectral Methods John P. Boyd, 2001-12-03 Completely revised text focuses on use of spectral methods to solve boundary value, eigenvalue, and time-dependent problems, but also covers Hermite, Laguerre, rational Chebyshev, sinc, and spherical harmonic functions, as well as cardinal functions, linear eigenvalue problems, matrix-solving methods, coordinate transformations, methods for unbounded intervals, spherical and cylindrical geometry, and much more. 7 Appendices. Glossary. Bibliography. Index. Over 160 text figures. |
| spectral analysis for physical applications: Random Vibration and Spectral Analysis/Vibrations aléatoires et analyse spectral A. Preumont, 2013-06-29 I became interested in Random Vibration during the preparation of my PhD dissertation, which was concerned with the seismic response of nuclear reactor cores. I was initiated into this field through the cla.ssical books by Y.K.Lin, S.H.Crandall and a few others. After the completion of my PhD, in 1981, my supervisor M.Gera.din encouraged me to prepare a course in Random Vibration for fourth and fifth year students in Aeronautics, at the University of Liege. There was at the time very little material available in French on that subject. A first draft was produced during 1983 and 1984 and revised in 1986. These notes were published by the Presses Poly techniques et Universitaires Romandes (Lausanne, Suisse) in 1990. When Kluwer decided to publish an English translation ofthe book in 1992, I had to choose between letting Kluwer translate the French text in-extenso or doing it myself, which would allow me to carry out a sustantial revision of the book. I took the second option and decided to rewrite or delete some of the original text and include new material, based on my personal experience, or reflecting recent technical advances. Chapter 6, devoted to the response of multi degree offreedom structures, has been completely rewritten, and Chapter 11 on random fatigue is entirely new. The computer programs which have been developed in parallel with these chapters have been incorporated in the general purpose finite element software SAMCEF, developed at the University of Liege. |
| spectral analysis for physical applications: Modern Spectral Estimation Steven M. Kay, 1988 |
| spectral analysis for physical applications: Introduction to Spectral Theory in Hilbert Space Gilbert Helmberg, 2014-11-28 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. |
| spectral analysis for physical applications: Time Series Analysis and Its Applications Robert H. Shumway, David S. Stoffer, 2013-03-14 The goals of this book are to develop an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing data, and still maintain a commitment to theoretical integrity, as exemplified by the seminal works of Brillinger (1981) and Hannan (1970) and the texts by Brockwell and Davis (1991) and Fuller (1995). The advent of more powerful computing, es pecially in the last three years, has provided both real data and new software that can take one considerably beyond the fitting of·simple time domain mod els, such as have been elegantly described in the landmark work of Box and Jenkins (1970). The present book is designed to be useful as a text for courses in time series on several different levels and as a reference work for practition ers facing the analysis of time-correlated data in the physical, biological, and social sciences. We believe the book will be useful as a text at both the undergraduate and graduate levels. An undergraduate course can be accessible to students with a background in regression analysis and might include Sections 1. 1-1. 8, 2. 1-2. 9, and 3. 1-3. 8. Similar courses have been taught at the University of California (Berkeley and Davis) in the past using the earlier book on applied time series analysis by Shumway (1988). Such a course is taken by undergraduate students in mathematics, economics, and statistics and attracts graduate students from the agricultural, biological, and environmental sciences. |
| spectral analysis for physical applications: Applied Mathematics Charles K. Chui, Qingtang Jiang, 2013-10-01 This textbook, apart from introducing the basic aspects of applied mathematics, focuses on recent topics such as information data manipulation, information coding, data approximation, data dimensionality reduction, data compression, time-frequency and time scale bases, image manipulation, and image noise removal. The methods treated in more detail include spectral representation and “frequency” of the data, providing valuable information for, e.g. data compression and noise removal. Furthermore, a special emphasis is also put on the concept of “wavelets” in connection with the “multi-scale” structure of data-sets. The presentation of the book is elementary and easily accessible, requiring only some knowledge of elementary linear algebra and calculus. All important concepts are illustrated with examples, and each section contains between 10 an 25 exercises. A teaching guide, depending on the level and discipline of instructions is included for classroom teaching and self-study. |
| spectral analysis for physical applications: Infrared Spectroscopy Barbara H. Stuart, 2004-08-20 Provides an introduction to those needing to use infrared spectroscopy for the first time, explaining the fundamental aspects of this technique, how to obtain a spectrum and how to analyse infrared data covering a wide range of applications. Includes instrumental and sampling techniques Covers biological and industrial applications Includes suitable questions and problems in each chapter to assist in the analysis and interpretation of representative infrared spectra Part of the ANTS (Analytical Techniques in the Sciences) Series. |
| spectral analysis for physical applications: Mathematical Analysis and Numerical Methods for Science and Technology Robert Dautray, Jacques-Louis Lions, 2012-12-06 These 6 volumes -- the result of a 10 year collaboration between the authors, both distinguished international figures -- compile the mathematical knowledge required by researchers in mechanics, physics, engineering, chemistry and other branches of application of mathematics for the theoretical and numerical resolution of physical models on computers. The advent of high-speed computers has made it possible to calculate values from models accurately and rapidly. Researchers and engineers thus have a crucial means of using numerical results to modify and adapt arguments and experiments along the way. |
| spectral analysis for physical applications: Spectral Theory of Random Schrödinger Operators R. Carmona, J. Lacroix, 2012-12-06 Since the seminal work of P. Anderson in 1958, localization in disordered systems has been the object of intense investigations. Mathematically speaking, the phenomenon can be described as follows: the self-adjoint operators which are used as Hamiltonians for these systems have a ten dency to have pure point spectrum, especially in low dimension or for large disorder. A lot of effort has been devoted to the mathematical study of the random self-adjoint operators relevant to the theory of localization for disordered systems. It is fair to say that progress has been made and that the un derstanding of the phenomenon has improved. This does not mean that the subject is closed. Indeed, the number of important problems actually solved is not larger than the number of those remaining. Let us mention some of the latter: • A proof of localization at all energies is still missing for two dimen sional systems, though it should be within reachable range. In the case of the two dimensional lattice, this problem has been approached by the investigation of a finite discrete band, but the limiting pro cedure necessary to reach the full two-dimensional lattice has never been controlled. • The smoothness properties of the density of states seem to escape all attempts in dimension larger than one. This problem is particularly serious in the continuous case where one does not even know if it is continuous. |
| spectral analysis for physical applications: Tensor Analysis Liqun Qi, Ziyan Luo, 2017-04-19 Tensors, or hypermatrices, are multi-arrays with more than two indices. In the last decade or so, many concepts and results in matrix theory?some of which are nontrivial?have been extended to tensors and have a wide range of applications (for example, spectral hypergraph theory, higher order Markov chains, polynomial optimization, magnetic resonance imaging, automatic control, and quantum entanglement problems). The authors provide a comprehensive discussion of this new theory of tensors. Tensor Analysis: Spectral Theory and Special Tensors is unique in that it is the first book on these three subject areas: spectral theory of tensors; the theory of special tensors, including nonnegative tensors, positive semidefinite tensors, completely positive tensors, and copositive tensors; and the spectral hypergraph theory via tensors. |
| spectral analysis for physical applications: Statistical Data Analysis for the Physical Sciences Adrian Bevan, 2013-05-09 A modern introduction to statistics for undergraduates in physics, with worked examples and case studies to illustrate techniques presented. |
| spectral analysis for physical applications: Persistent Spectral Hole-Burning: Science and Applications William E. Moerner, 2012-12-06 Almost fifteen years have now elapsed since the first observations of per sistent spectral hole-burning in inhomogeneously broadened absorption lines in solids. The fact that the spectral shape of an inhomogeneously broadened line can be locally modified for long periods of time has led to a large number of investigations of low-temperature photophysics and photochemistry that would not have been possible otherwise. Using hole burning, important information has been obtained about a variety of in teractions, including excited-state dephasing processes, host-guest dynam ics, proton tunnelling, low-frequency excitation in amorphous hosts, relaxation mechanisms for vibrational modes, photochemical mechanisms at liquid helium temperatures, and external field perturbations. At the same time, the possibility that persistent spectral holes might be used to store digital information has led to the study of materials and configura tions for frequency-domain optical storage and related possible applica tions. This is the first full-length book on persistent spectral hole-burning. The goal is to provide a broadly based survey of the scientific principles and applications of persistent spectral hole-burning. Since the topic is quite interdisciplinary, the book is intended for researchers, graduate stu dents, and advanced undergraduates in the fields of chemical physics, solid-state physics, laser spectroscopy, solid-state photochemistry, and high-performance optical storage and optical processing. |
| spectral analysis for physical applications: Bayesian Spectrum Analysis and Parameter Estimation G. Larry Bretthorst, 2013-03-09 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. |
| spectral analysis for physical applications: Automatic Autocorrelation and Spectral Analysis Piet M. T. Broersen, 2006-04-20 Automatic Autocorrelation and Spectral Analysis gives random data a language to communicate the information they contain objectively. It takes advantage of greater computing power and robust algorithms to produce enough candidate models of a given group of data to be sure of providing a suitable one. Improved order selection guarantees that one of the best (often the best) will be selected automatically. Written for graduate signal processing students and for researchers and engineers using time series analysis for applications ranging from breakdown prevention in heavy machinery to measuring lung noise for medical diagnosis, this text offers: - tuition in how power spectral density and the autocorrelation function of stochastic data can be estimated and interpreted in time series models; - extensive support for the MATLAB® ARMAsel toolbox; - applications showing the methods in action; - appropriate mathematics for students to apply the methods with references for those who wish to develop them further. |
| spectral analysis for physical applications: Compositional Data Analysis Vera Pawlowsky-Glahn, Antonella Buccianti, 2011-09-19 It is difficult to imagine that the statistical analysis of compositional data has been a major issue of concern for more than 100 years. It is even more difficult to realize that so many statisticians and users of statistics are unaware of the particular problems affecting compositional data, as well as their solutions. The issue of ``spurious correlation'', as the situation was phrased by Karl Pearson back in 1897, affects all data that measures parts of some whole, such as percentages, proportions, ppm and ppb. Such measurements are present in all fields of science, ranging from geology, biology, environmental sciences, forensic sciences, medicine and hydrology. This book presents the history and development of compositional data analysis along with Aitchison's log-ratio approach. Compositional Data Analysis describes the state of the art both in theoretical fields as well as applications in the different fields of science. Key Features: Reflects the state-of-the-art in compositional data analysis. Gives an overview of the historical development of compositional data analysis, as well as basic concepts and procedures. Looks at advances in algebra and calculus on the simplex. Presents applications in different fields of science, including, genomics, ecology, biology, geochemistry, planetology, chemistry and economics. Explores connections to correspondence analysis and the Dirichlet distribution. Presents a summary of three available software packages for compositional data analysis. Supported by an accompanying website featuring R code. Applied scientists working on compositional data analysis in any field of science, both in academia and professionals will benefit from this book, along with graduate students in any field of science working with compositional data. |
| spectral analysis for physical applications: Concise Handbook Of Analytical Spectroscopy, The: Theory, Applications, And Reference Materials (In 5 Volumes) Jerome (Jerry) James Workman, Jr, 2016-06-17 The concept of improving the use of electromagnetic energy to achieve a variety of qualitative and quantitative spectroscopic measurements on solid and liquid materials has been proliferating at a rapid rate. The use of such technologies to measure chemical composition, appearance, for classification, and to achieve detailed understanding of material interactions has prompted a dramatic expansion in the use and development of spectroscopic techniques over a variety of academic and commercial fields.The Concise Handbook of Analytical Spectroscopy is integrated into 5 volumes, each covering the theory, instrumentation, sampling methods, experimental design, and data analysis techniques, as well as essential reference tables, figures, and spectra for each spectroscopic region. The detailed practical aspects of applying spectroscopic tools for many of the most exciting and current applications are covered. Featured applications include: medical, biomedical, optical, physics, common commercial analysis methods, spectroscopic quantitative and qualitative techniques, and advanced methods.This multi-volume handbook is designed specifically as a reference tool for students, commercial development and quality scientists, and researchers or technologists in a variety of measurement endeavours.Number of Illustrations and Tables: 393 b/w illus., 304 colour illus, 413 tables.Related Link(s) |
| spectral analysis for physical applications: Handbook of Environmental and Ecological Statistics Alan E. Gelfand, Montserrat Fuentes, Jennifer A. Hoeting, Richard Lyttleton Smith, 2019-01-15 This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science. |
| spectral analysis for physical applications: Adaptive Radar Signal Processing Simon Haykin, 2006-11-10 This collaborative work presents the results of over twenty years of pioneering research by Professor Simon Haykin and his colleagues, dealing with the use of adaptive radar signal processing to account for the nonstationary nature of the environment. These results have profound implications for defense-related signal processing and remote sensing. References are provided in each chapter guiding the reader to the original research on which this book is based. |
| spectral analysis for physical applications: Quantitative Methods of Data Analysis for the Physical Sciences and Engineering Douglas G. Martinson, 2018-04-30 This book provides thorough and comprehensive coverage of most of the new and important quantitative methods of data analysis for graduate students and practitioners. In recent years, data analysis methods have exploded alongside advanced computing power, and it is critical to understand such methods to get the most out of data, and to extract signal from noise. The book excels in explaining difficult concepts through simple explanations and detailed explanatory illustrations. Most unique is the focus on confidence limits for power spectra and their proper interpretation, something rare or completely missing in other books. Likewise, there is a thorough discussion of how to assess uncertainty via use of Expectancy, and the easy to apply and understand Bootstrap method. The book is written so that descriptions of each method are as self-contained as possible. Many examples are presented to clarify interpretations, as are user tips in highlighted boxes. |
| spectral analysis for physical applications: Signal Processing James Vincent Candy, 2024-10-15 Separate signals from noise with this valuable introduction to signal processing by applied decomposition The decomposition of complex signals into the sub-signals, or individual components, is a crucial tool in signal processing. It allows each component of a signal to be analyzed individually, enables the signal to be isolated from noise, and processed in full. Decomposition processes have not always been widely adopted due to the difficult underlying mathematics and complex applications. This text simplifies these obstacles. Signal Processing: An Applied Decomposition Approach demystifies these tools from a model-based perspective. This offers a mathematically informed, “step-by-step” analysis of the process by breaking down a composite signal/system into its constituent parts, while introducing both fundamental concepts and advanced applications. This comprehensive approach addresses each of the major decomposition techniques, making it an indispensable addition to any library specializing in signal processing. Signal Processing readers will find: Signal decomposition techniques developed from the data-based, spectral-based and model-based perspectives incorporate: statistical approaches (PCA, ICA, Singular Spectrum); spectral approaches (MTM, PHD, MUSIC); and model-based approaches (EXP, LATTICE, SSP) In depth discussion of topics includes signal/system estimation and decomposition, time domain and frequency domain techniques, systems theory, modal decompositions, applications and many more Numerous figures, examples, and tables illustrating key concepts and algorithms are developed throughout the text Includes problem sets, case studies, real-world applications as well as MATLAB notes highlighting applicable commands Signal Processing is ideal for engineering and scientific professionals, as well as graduate students seeking a focused text on signal/system decomposition with performance metrics and real-world applications. |
| spectral analysis for physical applications: Spectral Methods in Fluid Dynamics C. Canuto, 1988 |
| spectral analysis for physical applications: Random Processes in Physics and Finance Melvin Lax, Wei Cai, Min Xu, 2006-10-05 This text is aimed at students and professionals working on random processes in various areas, including physics and finance. The material presents the theoretical framework which Melvin Lax taught at the City University of New York from 1985 to 2001. |
如何评价电影《幽冥》(Spectral)？ - 知乎
Dec 9, 2016 · 我们前面说过，“Spectral”有两种意思，“光谱的”和“幽灵的”。 前一种意思指的是男主角马克发现，片中敌人是人类肉眼不可见的，但却可以在其他的光谱中看到；后一种意思是迷 …
谱域(spectral domain) 和频域(frequency domain) 有什么区别联系?
谱域(spectral domain) 和频域(frequency domain) 有什么区别联系? <草民(本科)是软件工程专业，信号与系统也只教授了简单的傅里叶变换> 最近导师让查阅 spectral domain CNN 相关的论 …
完全弄懂X射线光电子能谱（XPS） - 知乎
6 days ago · X射线光电子能谱（XPS）是一种用于分析材料表面化学成分和电子状态的先进技术。
信号进行频域分析，能提取哪些特征，有什么物理意义呢？ - 知乎
频率质心 （Spectral centroid），这个比较容易理解，就说对于整个频率带去一个几何平均值，作用类似于物理上的质量之心：用一个点来代表整个质量。 这个同理，用一个频率来代表整个 …
紫外可见吸收光谱图上吸收峰蓝移和红移的原因是什么？导致了什 …
西元 1842 年奥地利物理学家 C.J. Doppler 发现，当波源接近观察者的运动时，所发出的波就观测者而言似乎是堆聚起来，故观测到其波长变短；反之，当波源后退时，观测到波因扩散而波长 …
一文看懂索尼PS5 Pro相比PS5升级了哪些配置，PS5 Pro是否值得购 …
May 28, 2025 · 还有就是最近火热的AI功能，PS5 Pro新增了名字为“PlayStation Spectral Super Resolution（PSSR）”的AI 超分辨率技术，类似英伟达 DLSS 或 AMD 的 FSR，可在增强画 …
有问题，就会有答案 - 知乎
知乎，中文互联网高质量的问答社区和创作者聚集的原创内容平台，于 2011 年 1 月正式上线，以「让人们更好的分享知识、经验和见解，找到自己的解答」为品牌使命。知乎凭借认真、专业 …
有哪些数据库可以查询各种物质的紫外、红外等吸收光谱？ - 知乎
Spectral Database for Organic Compounds (SDBS) SDBS 是由日本国立材料与化学研究所维护的光谱数据库，包含广泛的 NMR、MS、IR 和紫外可见光谱数据。 该数据库可以免费使用。
OpenAI 上线新一代编程神器 Codex，有哪些技术亮点？程序员的 …
这次问题是修复Bug：在mlab._spectral_helper中的窗口校正（windows correction）不正确。 同样可以看到，Codex修改代码的过程更为简洁。 django
LaTeX 如何插入图片？ - 知乎
在LaTeX中插入图片需要用到graphicx宏包，该宏包提供了\includegraphics命令，可以将图片插入到文档中。
如何评价电影《幽冥》(Spectral)？ - 知乎
Dec 9, 2016 · 我们前面说过，“Spectral”有两种意思，“光谱的”和“幽灵的”。 前一种意思指的是男主角马克发现，片中敌人是人类肉眼不可见的，但却可以在其他的光谱中看到；后一种意思是迷 …
谱域(spectral domain) 和频域(frequency domain) 有什么区别联系?
谱域(spectral domain) 和频域(frequency domain) 有什么区别联系? <草民(本科)是软件工程专业，信号与系统也只教授了简单的傅里叶变换> 最近导师让查阅 spectral domain CNN 相关的论 …
完全弄懂X射线光电子能谱（XPS） - 知乎
6 days ago · X射线光电子能谱（XPS）是一种用于分析材料表面化学成分和电子状态的先进技术。
信号进行频域分析，能提取哪些特征，有什么物理意义呢？ - 知乎
频率质心 （Spectral centroid），这个比较容易理解，就说对于整个频率带去一个几何平均值，作用类似于物理上的质量之心：用一个点来代表整个质量。 这个同理，用一个频率来代表整个 …
紫外可见吸收光谱图上吸收峰蓝移和红移的原因是什么？导致了什 …
西元 1842 年奥地利物理学家 C.J. Doppler 发现，当波源接近观察者的运动时，所发出的波就观测者而言似乎是堆聚起来，故观测到其波长变短；反之，当波源后退时，观测到波因扩散而波长 …
一文看懂索尼PS5 Pro相比PS5升级了哪些配置，PS5 Pro是否值得购 …
May 28, 2025 · 还有就是最近火热的AI功能，PS5 Pro新增了名字为“PlayStation Spectral Super Resolution（PSSR）”的AI 超分辨率技术，类似英伟达 DLSS 或 AMD 的 FSR，可在增强画 …
有问题，就会有答案 - 知乎
知乎，中文互联网高质量的问答社区和创作者聚集的原创内容平台，于 2011 年 1 月正式上线，以「让人们更好的分享知识、经验和见解，找到自己的解答」为品牌使命。知乎凭借认真、专业 …
有哪些数据库可以查询各种物质的紫外、红外等吸收光谱？ - 知乎
Spectral Database for Organic Compounds (SDBS) SDBS 是由日本国立材料与化学研究所维护的光谱数据库，包含广泛的 NMR、MS、IR 和紫外可见光谱数据。 该数据库可以免费使用。
OpenAI 上线新一代编程神器 Codex，有哪些技术亮点？程序员的 …
这次问题是修复Bug：在mlab._spectral_helper中的窗口校正（windows correction）不正确。 同样可以看到，Codex修改代码的过程更为简洁。 django
LaTeX 如何插入图片？ - 知乎
在LaTeX中插入图片需要用到graphicx宏包，该宏包提供了\includegraphics命令，可以将图片插入到文档中。
