Download or read book ADVANCED SPECTRAL ANALYSIS written by Dr. Prince Prashant Sharma and published by JEC PUBLICATION. This book was released on with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral analysis is an intricate field that holds the key to understanding a wide range of phenomena across science and engineering. "ADVANCED SPECTRAL ANALYSIS (MPC 201T)" is a comprehensive exploration of this subject, aimed at providing both beginners and experienced practitioners with a deep and practical understanding of spectral analysis techniques. This book is the culmination of extensive research, countless hours of analysis, and the collaboration of numerous experts in the field. It is our intention to bridge the gap between theory and application, offering readers a valuable resource that can be applied to real-world challenges. Throughout these pages, you will find a structured journey into the world of spectral analysis. We delve into the fundamental concepts, mathematical foundations, and advanced techniques, all with the aim of enabling you to make informed and insightful decisions when dealing with spectral data. This knowledge is not just for academics and researchers; it is for engineers, scientists, and anyone seeking a deeper appreciation of the spectral realm. Our approach is to combine theory with practical examples, providing step-by-step guidance on applying spectral analysis to a multitude of scenarios. We believe in demystifying the complex and making the abstract accessible. In this ever-evolving field, our commitment to the reader is to provide a resource that remains relevant and up-to-date. Spectral analysis is not just a subject; it's a living and dynamic field, and we invite you to embark on this journey of discovery with us. We extend our sincere gratitude to all those who have contributed to this endeavor, from researchers and experts to friends and family, whose support and encouragement have been invaluable. This book would not have been possible without your collective efforts.
Download or read book Advanced Spectral Analysis with Applications written by Niclas Sandgren and published by . This book was released on 2007 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Spectral Analysis of Signals written by Petre Stoica and published by Prentice Hall. This book was released on 2005 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed for introductory courses on Spectral Analysis at the graduate or advanced undergraduate level for students, researchers, and practitioners in the area of Signal Processing, this text is an expanded edition of "Introduction to Spectral Analysis". It includes nonparametric spectrum analysis, parametric spectral analysis and parametric met.
Download or read book Multi scale Spectral Analysis in Hydrology written by Adarsh S and published by CRC Press. This book was released on 2021-02-28 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Spectral Analysis of Time Series written by L. H. Koopmans and published by Academic Press. This book was released on 2014-05-12 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Spectral Analysis of Time Series describes the techniques and theory of the frequency domain analysis of time series. The book discusses the physical processes and the basic features of models of time series. The central feature of all models is the existence of a spectrum by which the time series is decomposed into a linear combination of sines and cosines. The investigator can used Fourier decompositions or other kinds of spectrals in time series analysis. The text explains the Wiener theory of spectral analysis, the spectral representation for weakly stationary stochastic processes, and the real spectral representation. The book also discusses sampling, aliasing, discrete-time models, linear filters that have general properties with applications to continuous-time processes, and the applications of multivariate spectral models. The text describes finite parameter models, the distribution theory of spectral estimates with applications to statistical inference, as well as sampling properties of spectral estimates, experimental design, and spectral computations. The book is intended either as a textbook or for individual reading for one-semester or two-quarter course for students of time series analysis users. It is also suitable for mathematicians or professors of calculus, statistics, and advanced mathematics.
Download or read book Digital Spectral Analysis written by Francis Castanié and published by John Wiley & Sons. This book was released on 2013-02-04 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature. The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models. An entire chapter is devoted to the non-parametric methods most widely used in industry. High resolution methods are detailed in a further four chapters: spectral analysis by stationary time series modeling, minimum variance, and subspace-based estimators. Finally, advanced concepts are the core of the last four chapters: spectral analysis of non-stationary random signals, space time adaptive processing: irregularly sampled data processing, particle filtering and tracking of varying sinusoids. Suitable for students, engineers working in industry, and academics at any level, this book provides a rare complete overview of the spectral analysis domain.
Download or read book Introduction to Spectral Analysis written by Petre Stoica and published by Pearson Education. This book was released on 1997 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an introduction to spectral analysis that is designed for either course use or self-study. Clear and concise in approach, it develops a firm understanding of tools and techniques as well as a solid background for performing research. Topics covered include nonparametric spectrum analysis (both periodogram-based approaches and filter- bank approaches), parametric spectral analysis using rational spectral models (AR, MA, and ARMA models), parametric method for line spectra, and spatial (array) signal processing. Analytical and Matlab-based computer exercises are included to develop both analytical skills and hands-on experience.
Download or read book Spectral Analysis for Physical Applications written by Donald B. Percival and published by Cambridge University Press. This book was released on 1993-06-03 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an up-to-date introduction to univariate spectral analysis at the graduate level, which reflects a new scientific awareness of spectral complexity, as well as the widespread use of spectral analysis on digital computers with considerable computational power. The text provides theoretical and computational guidance on the available techniques, emphasizing those that work in practice. Spectral analysis finds extensive application in the analysis of data arising in many of the physical sciences, ranging from electrical engineering and physics to geophysics and oceanography. A valuable feature of the text is that many examples are given showing the application of spectral analysis to real data sets. Special emphasis is placed on the multitaper technique, because of its practical success in handling spectra with intricate structure, and its power to handle data with or without spectral lines. The text contains a large number of exercises, together with an extensive bibliography.
Download or read book Multi scale Spectral Analysis in Hydrology written by Adarsh S and published by CRC Press. This book was released on 2021-03-01 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Digital Spectral Analysis written by S. Lawrence Marple, Jr. and published by Courier Dover Publications. This book was released on 2019-03-20 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital Spectral Analysis offers a broad perspective of spectral estimation techniques and their implementation. Coverage includes spectral estimation of discrete-time or discrete-space sequences derived by sampling continuous-time or continuous-space signals. The treatment emphasizes the behavior of each spectral estimator for short data records and provides over 40 techniques described and available as implemented MATLAB functions. In addition to summarizing classical spectral estimation, this text provides theoretical background and review material in linear systems, Fourier transforms, matrix algebra, random processes, and statistics. Topics include Prony's method, parametric methods, the minimum variance method, eigenanalysis-based estimators, multichannel methods, and two-dimensional methods. Suitable for advanced undergraduates and graduate students of electrical engineering — and for scientific use in the signal processing application community outside of universities — the treatment's prerequisites include some knowledge of discrete-time linear system and transform theory, introductory probability and statistics, and linear algebra. 1987 edition.
Download or read book Advanced Spectral spatial Processing Techniques for Hyperspectral Image Analysis written by Tong Qiao and published by . This book was released on 2016 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this research is to design and implement novel spectral-spatial processing techniques for hyperspectral image analysis and applications. Although the high dimensionality of hyperspectral image data makes its transmission and storage difficult, the uncompressed data format is still preferred as it avoids compression loss which may degrade classification accuracy. In this thesis, a quality-assured lossy compression scheme based on a modified three dimensional discrete cosine transform is proposed. This novel technique is demonstrated to maintain the integrity of hyperspectral data without degrading the classification accuracy. Furthermore, this work has led to the creation of an effective spectral feature extraction technique which uses curvelet transform and singular spectrum analysis. In addition to this, an original classification framework which combines joint bilateral filtering and an improved sparse representation classifier is presented. Experimental results show that the proposed methodologies outperform most of the state-of-the-art feature extraction and classification techniques commonly employed in the hyperspectral community. This work also demonstrates that hyperspectral imaging combined with advanced signal processing is an effective technology for food quality control applications. For example, when applied to the challenge of performing hyperspectral imaging-based meat quality assessment, the techniques proposed in this work are shown to provide a more effective solution than conventional visible and near-infrared spectroscopic technology. Finally, this thesis provides the first set of results of assessing the quality of beef and lamb samples using an improved data regression technique. To sum up, the outcome of this thesis advances the hyperspectral imaging community by proposing several novel methodologies, and extensive experiments have been conducted to demonstrate their superiority.
Download or read book Advances in Spectrum Analysis and Array Processing written by Simon S. Haykin and published by . This book was released on 1991 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Digital Signal Processing and Spectral Analysis for Scientists written by Silvia Maria Alessio and published by Springer. This book was released on 2015-12-09 with total page 909 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the basics of processing and spectral analysis of monovariate discrete-time signals. The approach is practical, the aim being to acquaint the reader with the indications for and drawbacks of the various methods and to highlight possible misuses. The book is rich in original ideas, visualized in new and illuminating ways, and is structured so that parts can be skipped without loss of continuity. Many examples are included, based on synthetic data and real measurements from the fields of physics, biology, medicine, macroeconomics etc., and a complete set of MATLAB exercises requiring no previous experience of programming is provided. Prior advanced mathematical skills are not needed in order to understand the contents: a good command of basic mathematical analysis is sufficient. Where more advanced mathematical tools are necessary, they are included in an Appendix and presented in an easy-to-follow way. With this book, digital signal processing leaves the domain of engineering to address the needs of scientists and scholars in traditionally less quantitative disciplines, now facing increasing amounts of data.
Download or read book Advanced Spectral Analysis Methods for Quantification of Coherent Ultrasound Scattering written by and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this dissertation was to improve the diagnostic value of parametric images generated from Quantitative Ultrasound (QUS) methods based on the power spectral density (PSD) of radiofrequency echo signals. This was achieved by testing for local adherence to conventional QUS assumptions that echo signals originate from incoherent scattering, and that signals are stationary over PSD estimation windows. For this purpose, we designed a novel algorithm that empirically evaluates the statistical significance of coherent-scattering signatures in the echo signals. Signatures are quantified through a set of optimized metrics describing the stationary or non-stationary features of the echo signals. We compared Nakagami-model based metrics and model-free metrics of the statistics of the echo signal amplitude for analyzing stationary features. For non-stationary features, we advanced the use of the echo-signal generalized spectrum by comparing single- and multi-taper estimators of this spectrum to the time-domain singular spectrum analysis method. Tests of statistical significance were done through empirical comparisons with values of the same metrics estimated from a uniform reference material exhibiting incoherent scattering. The metrics that quantify these features were selected after simulation- and phantom-based optimizations centered on the task of creating parametric images, where tradeoffs must be made between spatial resolution and detection performance. The connection of the analyses of the stationary and the non-stationary features provided a way to estimate descriptors of the tissue organization scales below and above the resolution limit imposed by the size of the acoustic pulse. A preliminary application of the developed algorithm was done on echo data from human breast lesions scanned in vivo. Results supported the idea of a more homogeneously random distribution of subresolution scatterers within invasive ductal carcinomas than within fibroadenomas. Results also indicated the importance of the anisotropy of the scattering process to distinguish between different lesion types. Future work will refine the tools developed here and explore the connections between these backscattered echo characteristics and tissue microstructure studied through microscopy.
Download or read book Biointerface Characterization by Advanced IR Spectroscopy written by C.-M. Pradier and published by Elsevier. This book was released on 2011-09-02 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: "There is an increasing interest in research and applications of biosensors and bio-compatability in relation to environmental protection, food and medical safety, implants, early detection of diseases and pollutant detection. This book describes how to characterise amino acids, protein or bacterial strain adsorption on metal and oxide surfaces by using infrared spectroscopy, in a vacuum, in the air or in an aqueous medium. Features description of the principles, experimental setups and parameter interpretation, and the theory for several advanced IR-based techniques for interface characterisation Contains examples which demonstrate the capacity, potential and limits of the IR techniques Helps finding the most adequate mode of analysis."--Publisher.
Download or read book Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation written by Prasad S. Thenkabail and published by CRC Press. This book was released on 2018-12-07 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume IV, Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation discusses the use of hyperspectral or imaging spectroscopy data in numerous specific and advanced applications, such as forest management, precision farming, managing invasive species, and local to global land cover change detection. It emphasizes the importance of hyperspectral remote sensing tools for studying vegetation processes and functions as well as the appropriate use of hyperspectral data for vegetation management practices. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume IV through the editors’ perspective. Key Features of Volume IV: Guides readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation. Includes specific applications on agriculture, crop management practices, study of crop stress and diseases, crop characteristics based on inputs (e.g., nitrogen, irrigation), study of vegetation impacted by heavy metals, gross and net primary productivity studies, light use efficiency studies, crop water use and actual evapotranspiration studies, phenology monitoring, land use and land cover studies, global change studies, plant species detection, wetland and forest characterization and mapping, crop productivity and crop water productivity mapping, and modeling. Encompasses hyperspectral or imaging spectroscopy data in narrow wavebands used across visible, red-edge, near-infrared, far-infrared, shortwave infrared, and thermal portions of the spectrum. Explains the implementation of hyperspectral remote sensing data processing mechanisms in a standard, fast, and efficient manner for their applications. Discusses cloud computing to overcome hyperspectral remote sensing massive big data challenges. Provides hyperspectral analysis of rocky surfaces on the earth and other planetary systems.
Download or read book Advanced Digital Signal Processing and Noise Reduction written by Saeed V. Vaseghi and published by John Wiley & Sons. This book was released on 2008-12-23 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system. The fourth edition of Advanced Digital Signal Processing and Noise Reduction updates and extends the chapters in the previous edition and includes two new chapters on MIMO systems, Correlation and Eigen analysis and independent component analysis. The wide range of topics covered in this book include Wiener filters, echo cancellation, channel equalisation, spectral estimation, detection and removal of impulsive and transient noise, interpolation of missing data segments, speech enhancement and noise/interference in mobile communication environments. This book provides a coherent and structured presentation of the theory and applications of statistical signal processing and noise reduction methods. Two new chapters on MIMO systems, correlation and Eigen analysis and independent component analysis Comprehensive coverage of advanced digital signal processing and noise reduction methods for communication and information processing systems Examples and applications in signal and information extraction from noisy data Comprehensive but accessible coverage of signal processing theory including probability models, Bayesian inference, hidden Markov models, adaptive filters and Linear prediction models Advanced Digital Signal Processing and Noise Reduction is an invaluable text for postgraduates, senior undergraduates and researchers in the fields of digital signal processing, telecommunications and statistical data analysis. It will also be of interest to professional engineers in telecommunications and audio and signal processing industries and network planners and implementers in mobile and wireless communication communities.