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| digital spectral analysis with applications: Digital Spectral Analysis S. Lawrence Marple, 1987 |
| digital spectral analysis with applications: Digital Signal Processing and Spectral Analysis for Scientists Silvia Maria Alessio, 2015-12-09 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. |
| digital spectral analysis with 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. |
| digital spectral analysis with applications: Digital Spectral Analysis Francis Castanié, 2013-02-04 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. |
| digital spectral analysis with applications: Spectral Analysis and Filter Theory in Applied Geophysics Burkhard Buttkus, 2000-03-27 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. |
| digital spectral analysis with applications: Digital Spectral Analysis with Applications in C, FORTRAN, and MATLAB Stanley Lawrence Marple, 2010 |
| digital spectral analysis with applications: Principles of Random Signal Analysis and Low Noise Design Roy M. Howard, 2004-08-18 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. |
| digital spectral analysis with applications: Spectral Analysis and Its Applications Gwilym M. Jenkins, Donald G. Watts, 1968 |
| digital spectral analysis with applications: Digital Spectral Analysis MATLAB® Software User Guide S. Lawrence Marple, Jr., 2019-05-15 This user guide serves as a companion to Digital Spectral Analysis, Second Edition (Dover Publications, 2019), illustrating all the text's techniques and algorithms, plus time versus frequency analysis. The spectral demonstrations use MATLAB software that encompasses the full experience from inputting signal sources, interactively setting technique parameters and processing with those parameters, and choosing from a variety of plotting techniques to display the results. The processing functions and scripts have been coded to automatically handle sample data that is either real-valued or complex-valued, permitting the user to simply modify the demonstration scripts to input their own data for analysis. Four integrated software categories support the demonstrations. These are the main MATLAB spectral demonstration scripts, supporting MATLAB plotting scripts, MATLAB processing functions listed in this guide, and signal sample data sources. Scripts and demonstration data files can be found on the Dover website for free downloading; see the Introduction for details. |
| digital spectral analysis with applications: Window Functions and Their Applications in Signal Processing K. M. M. Prabhu, 2018-09-03 Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture radar |
| digital spectral analysis with 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. |
| digital spectral analysis with applications: Spectral Logic and Its Applications for the Design of Digital Devices Mark G. Karpovsky, Radomir S. Stankovic, Jaakko T. Astola, 2008-07-14 Spectral techniques facilitate the design and testing of today's increasingly complex digital devices There is heightened interest in spectral techniques for the design of digital devices dictated by ever increasing demands on technology that often cannot be met by classical approaches. Spectral methods provide a uniform and consistent theoretic environment for recent achievements in this area, which appear divergent in many other approaches. Spectral Logic and Its Applications for the Design of Digital Devices gives readers a foundation for further exploration of abstract harmonic analysis over finite groups in the analysis, design, and testing of digital devices. After an introduction, this book provides the essential mathematical background for discussing spectral methods. It then delves into spectral logic and its applications, covering: * Walsh, Haar, arithmetic transform, Reed-Muller transform for binary-valued functions and Vilenkin-Chrestenson transform, generalized Haar, and other related transforms for multiple-valued functions * Polynomial expressions and decision diagram representations for switching and multiple-value functions * Spectral analysis of Boolean functions * Spectral synthesis and optimization of combinational and sequential devices * Spectral methods in analysis and synthesis of reliable devices * Spectral techniques for testing computer hardware This is the authoritative reference for computer science and engineering professionals and researchers with an interest in spectral methods of representing discrete functions and related applications in the design and testing of digital devices. It is also an excellent text for graduate students in courses covering spectral logic and its applications. |
| digital spectral analysis with applications: Spectral Analysis in Engineering Grant Hearn, Andrew Metcalfe, 1995-08-17 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 |
| digital spectral analysis with applications: Spectral Methods in Food Analysis Mossoba, 1998-11-11 Outlines the basic principles, advanced instrumentation, applications and future potential of a range of spectral techniques in food analysis. The book introduces new applications of GC-MS, LC-MS, MALDI TOF-MS, GC-FTIR, SFC-FTIR, ATR, and Raman spectroscopy. The book covers the identification and quantitation of food constituents, additives and contaminants. |
| digital spectral analysis with 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. |
| digital spectral analysis with applications: Spectral Audio Signal Processing Julius Orion Smith, 2007 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. |
| digital spectral analysis with applications: Starting Digital Signal Processing in Telecommunication Engineering Tomasz P. Zieliński, 2021-01-29 This hands-on, laboratory driven textbook helps readers understand principles of digital signal processing (DSP) and basics of software-based digital communication, particularly software-defined networks (SDN) and software-defined radio (SDR). In the book only the most important concepts are presented. Each book chapter is an introduction to computer laboratory and is accompanied by complete laboratory exercises and ready-to-go Matlab programs with figures and comments (available at the book webpage and running also in GNU Octave 5.2 with free software packages), showing all or most details of relevant algorithms. Students are tasked to understand programs, modify them, and apply presented concepts to recorded real RF signal or simulated received signals, with modelled transmission condition and hardware imperfections. Teaching is done by showing examples and their modifications to different real-world telecommunication-like applications. The book consists of three parts: introduction to DSP (spectral analysis and digital filtering), introduction to DSP advanced topics (multi-rate, adaptive, model-based and multimedia - speech, audio, video - signal analysis and processing) and introduction to software-defined modern telecommunication systems (SDR technology, analog and digital modulations, single- and multi-carrier systems, channel estimation and correction as well as synchronization issues). Many real signals are processed in the book, in the first part – mainly speech and audio, while in the second part – mainly RF recordings taken from RTL-SDR USB stick and ADALM-PLUTO module, for example captured IQ data of VOR avionics signal, classical FM radio with RDS, digital DAB/DAB+ radio and 4G-LTE digital telephony. Additionally, modelling and simulation of some transmission scenarios are tested in software in the book, in particular TETRA, ADSL and 5G signals. Provides an introduction to digital signal processing and software-based digital communication; Presents a transition from digital signal processing to software-defined telecommunication; Features a suite of pedagogical materials including a laboratory test-bed and computer exercises/experiments. |
| digital spectral analysis with 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. |
| digital spectral analysis with applications: Digital Signal Processing N. B. Jones, J. D. McK. Watson, 1990 This volume presents the fundamentals of data signal processing, ranging from data conversion to z-transforms and spectral analysis. In addition to presenting basic theory and describing the devices, the material is complemented by real examples in specific case studies. |
| digital spectral analysis with applications: Frequency Analysis R. B. Randall, 1987 |
| digital spectral analysis with 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. |
| digital spectral analysis with applications: Fundamentals of Spectrum Analysis Christoph Rauscher, Volker Janssen, Roland Minihold, 2007 |
| digital spectral analysis with applications: Digital Signal Processing Zahir M. Hussain, Amin Z. Sadik, Peter O’Shea, 2011-02-17 In three parts, this book contributes to the advancement of engineering education and that serves as a general reference on digital signal processing. Part I presents the basics of analog and digital signals and systems in the time and frequency domain. It covers the core topics: convolution, transforms, filters, and random signal analysis. It also treats important applications including signal detection in noise, radar range estimation for airborne targets, binary communication systems, channel estimation, banking and financial applications, and audio effects production. Part II considers selected signal processing systems and techniques. Core topics covered are the Hilbert transformer, binary signal transmission, phase-locked loops, sigma-delta modulation, noise shaping, quantization, adaptive filters, and non-stationary signal analysis. Part III presents some selected advanced DSP topics. |
| digital spectral analysis with applications: Biomedical Engineering Handbook Joseph D. Bronzino, 1999-12-28 Category Biomedical Engineering Subcategory Contact Editor: Stern |
| digital spectral analysis with applications: Signal Analysis Ronald L. Allen, Duncan Mills, 2004-06-07 Offers a well-rounded, mathematical approach to problems in signal interpretation using the latest time, frequency, and mixed-domain methods Equally useful as a reference, an up-to-date review, a learning tool, and a resource for signal analysis techniques Provides a gradual introduction to the mathematics so that the less mathematically adept reader will not be overwhelmed with instant hard analysis Covers Hilbert spaces, complex analysis, distributions, random signals, analog Fourier transforms, and more |
| digital spectral analysis with applications: Handbook of Brain Connectivity Viktor K. Jirsa, A.R. McIntosh, 2007-08-16 Our contemporary understanding of brain function is deeply rooted in the ideas of the nonlinear dynamics of distributed networks. Cognition and motor coordination seem to arise from the interactions of local neuronal networks, which themselves are connected in large scales across the entire brain. The spatial architectures between various scales inevitably influence the dynamics of the brain and thereby its function. But how can we integrate brain connectivity amongst these structural and functional domains? Our Handbook provides an account of the current knowledge on the measurement, analysis and theory of the anatomical and functional connectivity of the brain. All contributors are leading experts in various fields concerning structural and functional brain connectivity. In the first part of the Handbook, the chapters focus on an introduction and discussion of the principles underlying connected neural systems. The second part introduces the currently available non-invasive technologies for measuring structural and functional connectivity in the brain. Part three provides an overview of the analysis techniques currently available and highlights new developments. Part four introduces the application and translation of the concepts of brain connectivity to behavior, cognition and the clinical domain. |
| digital spectral analysis with applications: Applications of Digital Signal Processing Christian Cuadrado-Laborde, 2011-11-23 In this book the reader will find a collection of chapters authored/co-authored by a large number of experts around the world, covering the broad field of digital signal processing. This book intends to provide highlights of the current research in the digital signal processing area, showing the recent advances in this field. This work is mainly destined to researchers in the digital signal processing and related areas but it is also accessible to anyone with a scientific background desiring to have an up-to-date overview of this domain. Each chapter is self-contained and can be read independently of the others. These nineteenth chapters present methodological advances and recent applications of digital signal processing in various domains as communications, filtering, medicine, astronomy, and image processing. |
| digital spectral analysis with applications: Discrete Random Signal Processing and Filtering Primer with MATLAB Alexander D. Poularikas, 2018-10-03 Engineers in all fields will appreciate a practical guide that combines several new effective MATLAB® problem-solving approaches and the very latest in discrete random signal processing and filtering. Numerous Useful Examples, Problems, and Solutions – An Extensive and Powerful Review Written for practicing engineers seeking to strengthen their practical grasp of random signal processing, Discrete Random Signal Processing and Filtering Primer with MATLAB provides the opportunity to doubly enhance their skills. The author, a leading expert in the field of electrical and computer engineering, offers a solid review of recent developments in discrete signal processing. The book also details the latest progress in the revolutionary MATLAB language. A Practical Self-Tutorial That Transcends Theory The author introduces an incremental discussion of signal processing and filtering, and presents several new methods that can be used for a more dynamic analysis of random digital signals with both linear and non-linear filtering. Ideal as a self-tutorial, this book includes numerous examples and functions, which can be used to select parameters, perform simulations, and analyze results. This concise guide encourages readers to use MATLAB functions – and those new ones introduced as Book MATLAB Functions – to substitute many different combinations of parameters, giving them a firm grasp of how much each parameter affects results. Much more than a simple review of theory, this book emphasizes problem solving and result analysis, enabling readers to take a hands-on approach to advance their own understanding of MATLAB and the way it is used within signal processing and filtering. |
| digital spectral analysis with applications: Fundamentals of Signal Processing in Generalized Metric Spaces Andrey Popoff, 2022-04-19 Exploring the interrelations between generalized metric spaces, lattice-ordered groups, and order statistics, the book contains a new algebraic approach to Signal Processing Theory. It describes mathematical concepts and results important in the development, analysis, and optimization of signal processing algorithms intended for various applications. The book offers a solution of large-scale Signal Processing Theory problems of increasing both signal processing efficiency under prior uncertainty conditions and signal processing rate that is provided by multiplication-free signal processing algorithms based on lattice-ordered group operations. From simple basic relationships to computer simulation, the text covers a wide range of new mathematical techniques essential for understanding the proposed signal processing algorithms developed for solving the following problems: signal parameter and spectral estimation, signal filtering, detection, classification, and resolution; array signal processing; demultiplexing and demodulation in multi-channel communication systems and multi-station networks; wavelet analysis of 1D/ 2D signals. Along with discussing mathematical aspects, each chapter presents examples illustrating operation of signal processing algorithms developed for various applications. The book helps readers understand relations between known classic and obtained results as well as recent research trends in Signal Processing Theory and its applications, providing all necessary mathematical background concerning lattice-ordered groups to prepare readers for independent work in the marked directions including more advanced research and development. |
| digital spectral analysis with applications: Fourier Analysis on Finite Groups and Applications Audrey Terras, 1999-03-28 It examines the theory of finite groups in a manner that is both accessible to the beginner and suitable for graduate research. |
| digital spectral analysis with applications: Advances in Nonlinear Geosciences Anastasios A. Tsonis, 2017-10-13 Advances in Nonlinear Geosciences is a set of contributions from the participants of “30 Years of Nonlinear Dynamics” held July 3-8, 2016 in Rhodes, Greece as part of the Aegean Conferences, as well as from several other experts in the field who could not attend the meeting. The volume brings together up-to-date research from the atmospheric sciences, hydrology, geology, and other areas of geosciences and presents the new advances made in the last 10 years. Topics include chaos synchronization, topological data analysis, new insights on fractals, multifractals and stochasticity, climate dynamics, extreme events, complexity, and causality, among other topics. |
| digital spectral analysis with applications: Shock and Vibration, Data Analysis and Applications Defense Documentation Center (U.S.), 1963 |
| digital spectral analysis with applications: An Introduction to Statistical Signal Processing Robert M. Gray, Lee D. Davisson, 2004-12-02 This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing using a range of carefully chosen examples. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book. Hundreds of homework problems are included and the book is ideal for graduate students of electrical engineering and applied mathematics. It is also a useful reference for researchers in signal processing and communications. |
| digital spectral analysis with applications: Advances in Spectrum Analysis and Array Processing Simon S. Haykin, 1991 This is the second of a two-volume set providing detailed discussion of fundamental issues in spectrum analysis and array processing, detailed treatments of popular and new algorithms in these fields and coverage of applications relevant to them. |
| digital spectral analysis with applications: Medical Devices and Systems Joseph D. Bronzino, 2006-04-19 Over the last century, medicine has come out of the black bag and emerged as one of the most dynamic and advanced fields of development in science and technology. Today, biomedical engineering plays a critical role in patient diagnosis, care, and rehabilitation. More than ever, biomedical engineers face the challenge of making sure that medical d |
| digital spectral analysis with applications: Encyclopedia of Biomaterials and Biomedical Engineering Gary Wnek, Gary Bowlin, 2008-05-28 Written by more than 400 subject experts representing diverse academic and applied domains, this multidisciplinary resource surveys the vanguard of biomaterials and biomedical engineering technologies utilizing biomaterials that lead to quality-of-life improvements. Building on traditional engineering principles, it serves to bridge advances in materials science, life sciences, nanotechnology, and cell biology to innovations in solving medical problems with applications in tissue engineering, prosthetics, drug delivery, biosensors, and medical devices. In nearly 300 entries, this four-volume Encyclopedia of Biomaterials and Biomedical Engineering, Second Edition, covers: essential topics integral to tissue engineering research: bioreactors, scaffolding materials and fabrication, tissue mechanics, cellular interaction, and development of major tissues and organs being attempted by researchers worldwide; artificial lungs and muscles, bio-artificial livers, and corneal, dental, inner ear, and total hip implants; tissue engineering of blood vessels, heart valves, ligaments, microvascular networks, skeletal muscle, and skin; bone remodeling, bone cement, and bioabsorbable bone plates and screws; controlled drug delivery, insulin delivery, and transdermal and ocular implant-based drug delivery; endovascular stent grafts, vascular grafts, and xenografts; 3-D medical imaging, electrical impedance imaging, and intravascular ultrasound; biomedical, protein adsorption, and in vivo cardiovascular modeling; polymer foams, biofunctional and conductive polymers, and electroactive polymeric materials; blood–material interactions, the bone–implant interface, host reactions, and foreign body responses and much more. |
| digital spectral analysis with applications: The Biomedical Engineering Handbook 1 Joseph D. Bronzino, 2000-02-15 |
| digital spectral analysis with applications: A Portable, Frequency-coherent Spectrum Analyzer for Radar Applications Ben B. Balsley, 1971 |
| digital spectral analysis with applications: Digital Signal Processing and Statistical Classification George J. Miao, Mark A. Clements, 2002 This is the first book to introduce and integrate advanced digital signal processing (DSP) and classification together, and the only volume to introduce state-of-the-art transforms including DFT, FFT, DCT, DHT, PCT, CDT, and ODT together for DSP and communication applications. You get step-by-step guidance in discrete-time domain signal processing and frequency domain signal analysis; digital filter design and adaptive filtering; multirate digital processing; and statistical signal classification. It also helps you overcome problems associated with multirate A/D and D/A converters. |
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