Spectral Analysis Of Signals

Author : Yanwei Wang,Jian Li,Petre Stoica
Publisher : Morgan & Claypool Publishers
Page : 103 pages
File Size : 48,5 Mb
Release : 2006-01-01
Category : Technology & Engineering
ISBN : 9781598290011

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Spectral Analysis of Signals by Yanwei Wang,Jian Li,Petre Stoica Pdf

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 : Petre Stoica,Randolph L. Moses
Publisher : Pearson Education
Page : 358 pages
File Size : 43,9 Mb
Release : 1997
Category : Mathematics
ISBN : UOM:39015049346268

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Introduction to Spectral Analysis by Petre Stoica,Randolph L. Moses Pdf

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.

Author : Silvia Maria Alessio
Publisher : Springer
Page : 900 pages
File Size : 44,6 Mb
Release : 2015-12-09
Category : Technology & Engineering
ISBN : 9783319254685

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Digital Signal Processing and Spectral Analysis for Scientists by Silvia Maria Alessio Pdf

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 : S. Lawrence Marple, Jr.
Publisher : Courier Dover Publications
Page : 435 pages
File Size : 41,6 Mb
Release : 2019-03-20
Category : Technology & Engineering
ISBN : 9780486780528

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Digital Spectral Analysis by S. Lawrence Marple, Jr. Pdf

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.

Author : Randolph L. Moses
Publisher : Unknown
Page : 452 pages
File Size : 44,5 Mb
Release : 2011
Category : Electronic
ISBN : 812034359X

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Spectral Analysis of Signals by Randolph L. Moses Pdf

Author : K. Deergha Rao,M.N.S. Swamy
Publisher : Springer
Page : 789 pages
File Size : 40,7 Mb
Release : 2018-04-14
Category : Mathematics
ISBN : 9789811080814

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Digital Signal Processing by K. Deergha Rao,M.N.S. Swamy Pdf

The book provides a comprehensive exposition of all major topics in digital signal processing (DSP). With numerous illustrative examples for easy understanding of the topics, it also includes MATLAB-based examples with codes in order to encourage the readers to become more confident of the fundamentals and to gain insights into DSP. Further, it presents real-world signal processing design problems using MATLAB and programmable DSP processors. In addition to problems that require analytical solutions, it discusses problems that require solutions using MATLAB at the end of each chapter. Divided into 13 chapters, it addresses many emerging topics, which are not typically found in advanced texts on DSP. It includes a chapter on adaptive digital filters used in the signal processing problems for faster acceptable results in the presence of changing environments and changing system requirements. Moreover, it offers an overview of wavelets, enabling readers to easily understand the basics and applications of this powerful mathematical tool for signal and image processing. The final chapter explores DSP processors, which is an area of growing interest for researchers. A valuable resource for undergraduate and graduate students, it can also be used for self-study by researchers, practicing engineers and scientists in electronics, communications, and computer engineering as well as for teaching one- to two-semester courses.

Author : Yanwei Wang,Jian Li,Petre Stoica
Publisher : Springer Nature
Page : 99 pages
File Size : 48,9 Mb
Release : 2022-05-31
Category : Technology & Engineering
ISBN : 9783031025259

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Spectral Analysis of Signals by Yanwei Wang,Jian Li,Petre Stoica Pdf

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 : Ljubiša Stanković,Ervin Sejdić
Publisher : Springer
Page : 507 pages
File Size : 53,8 Mb
Release : 2018-12-01
Category : Technology & Engineering
ISBN : 9783030035747

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Vertex-Frequency Analysis of Graph Signals by Ljubiša Stanković,Ervin Sejdić Pdf

This book introduces new methods to analyze vertex-varying graph signals. In many real-world scenarios, the data sensing domain is not a regular grid, but a more complex network that consists of sensing points (vertices) and edges (relating the sensing points). Furthermore, sensing geometry or signal properties define the relation among sensed signal points. Even for the data sensed in the well-defined time or space domain, the introduction of new relationships among the sensing points may produce new insights in the analysis and result in more advanced data processing techniques. The data domain, in these cases and discussed in this book, is defined by a graph. Graphs exploit the fundamental relations among the data points. Processing of signals whose sensing domains are defined by graphs resulted in graph data processing as an emerging field in signal processing. Although signal processing techniques for the analysis of time-varying signals are well established, the corresponding graph signal processing equivalent approaches are still in their infancy. This book presents novel approaches to analyze vertex-varying graph signals. The vertex-frequency analysis methods use the Laplacian or adjacency matrix to establish connections between vertex and spectral (frequency) domain in order to analyze local signal behavior where edge connections are used for graph signal localization. The book applies combined concepts from time-frequency and wavelet analyses of classical signal processing to the analysis of graph signals. Covering analytical tools for vertex-varying applications, this book is of interest to researchers and practitioners in engineering, science, neuroscience, genome processing, just to name a few. It is also a valuable resource for postgraduate students and researchers looking to expand their knowledge of the vertex-frequency analysis theory and its applications. The book consists of 15 chapters contributed by 41 leading researches in the field.

Author : Saeid Sanei,Hossein Hassani
Publisher : CRC Press
Page : 260 pages
File Size : 49,7 Mb
Release : 2015-12-23
Category : Medical
ISBN : 9781466589285

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Singular Spectrum Analysis of Biomedical Signals by Saeid Sanei,Hossein Hassani Pdf

Recent advancements in signal processing and computerised methods are expected to underpin the future progress of biomedical research and technology, particularly in measuring and assessing signals and images from the human body. This book focuses on singular spectrum analysis (SSA), an effective approach for single channel signal analysis, and its bivariate, multivariate, tensor based, complex-valued, quaternion-valued and robust variants. SSA currently has numerous applications in detecting abnormalities in quasi-periodic biosignals, such as electrocardiograms, (ECGs or EKGs), oxygen levels, arterial pressure, and electroencephalograms (EEGs). Singular Spectrum Analysis of Biomedical Signals presents relatively newly applied concepts for biomedical applications of SSA, including: Signal source separation, extraction, decomposition, and factorization Physiological, biological, and biochemical signal processing A new SSA grouping algorithm for filtering and noise reduction of genetics data Prediction of various clinical events The book introduces a new mathematical and signal processing technique for the decomposition of widely available single channel biomedical data. It also provides illustrations of new signal processing results in the form of signals, graphs, images, and tables to reinforce understanding of the related concepts. Singular Spectrum Analysis of Biomedical Signals enhances current clinical knowledge and aids physicians in improving diagnosis, treatment and monitoring some clinical abnormalities. It also lays groundwork for progress in SSA by making suggestions for future research.

Author : Roy M. Howard
Publisher : John Wiley & Sons
Page : 328 pages
File Size : 54,5 Mb
Release : 2004-08-18
Category : Technology & Engineering
ISBN : 9780471460831

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Principles of Random Signal Analysis and Low Noise Design by Roy M. Howard Pdf

Describes the leading techniques for analyzing noise. Discusses methods that are applicable to periodic signals,aperiodic signals, or random processes over finite or infiniteintervals. Provides readers with a useful reference when designing ormodeling communications systems.

Author : Mischa Schwartz,Leonard Shaw
Publisher : McGraw-Hill Companies
Page : 414 pages
File Size : 44,9 Mb
Release : 1975
Category : Science
ISBN : UOM:39015028286238

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Signal Processing: Discrete Spectral Analysis, Detection, and Estimation by Mischa Schwartz,Leonard Shaw Pdf

Author : Julius Orion Smith
Publisher : Unknown
Page : 654 pages
File Size : 55,9 Mb
Release : 2007
Category : Computer sound processing
ISBN : OCLC:637777935

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Spectral Audio Signal Processing by Julius Orion Smith Pdf

"Spectral Audio Signal Processing is the fourth book in the music signal processing series by Julius O. Smith. One can say that human hearing occurs in terms of spectral models. As a result, spectral models are especially useful in audio applications. For example, with the right spectral model, one can discard most of the information contained in a sound waveform without changing how it sounds. This is the basis of modern audio compression techniques."--Publisher's description.

Author : Sean A. Fulop
Publisher : Springer Science & Business Media
Page : 214 pages
File Size : 44,8 Mb
Release : 2011-05-26
Category : Technology & Engineering
ISBN : 9783642174780

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Speech Spectrum Analysis by Sean A. Fulop Pdf

The accurate determination of the speech spectrum, particularly for short frames, is commonly pursued in diverse areas including speech processing, recognition, and acoustic phonetics. With this book the author makes the subject of spectrum analysis understandable to a wide audience, including those with a solid background in general signal processing and those without such background. In keeping with these goals, this is not a book that replaces or attempts to cover the material found in a general signal processing textbook. Some essential signal processing concepts are presented in the first chapter, but even there the concepts are presented in a generally understandable fashion as far as is possible. Throughout the book, the focus is on applications to speech analysis; mathematical theory is provided for completeness, but these developments are set off in boxes for the benefit of those readers with sufficient background. Other readers may proceed through the main text, where the key results and applications will be presented in general heuristic terms, and illustrated with software routines and practical "show-and-tell" discussions of the results. At some points, the book refers to and uses the implementations in the Praat speech analysis software package, which has the advantages that it is used by many scientists around the world, and it is free and open source software. At other points, special software routines have been developed and made available to complement the book, and these are provided in the Matlab programming language. If the reader has the basic Matlab package, he/she will be able to immediately implement the programs in that platform---no extra "toolboxes" are required.

Author : Petrus M.T. Broersen
Publisher : Springer Science & Business Media
Page : 298 pages
File Size : 54,8 Mb
Release : 2006-08-02
Category : Technology & Engineering
ISBN : 9781846283291

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Automatic Autocorrelation and Spectral Analysis by Petrus M.T. Broersen Pdf

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.

Author : Simon S. Haykin
Publisher : Unknown
Page : 458 pages
File Size : 42,6 Mb
Release : 1991
Category : Signal processing
ISBN : UOM:39015021498608

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Advances in Spectrum Analysis and Array Processing by Simon S. Haykin Pdf