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Hilbert Space Methods In Signal Processing
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Book Synopsis Hilbert Space Methods in Signal Processing by : Rodney A. Kennedy
Download or read book Hilbert Space Methods in Signal Processing written by Rodney A. Kennedy and published by Cambridge University Press. This book was released on 2013-03-07 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible introduction to Hilbert spaces, combining the theory with applications of Hilbert methods in signal processing.
Book Synopsis Foundations of Signal Processing by : Martin Vetterli
Download or read book Foundations of Signal Processing written by Martin Vetterli and published by Cambridge University Press. This book was released on 2014-09-04 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications. Students are introduced to the powerful foundations of modern signal processing, including the basic geometry of Hilbert space, the mathematics of Fourier transforms, and essentials of sampling, interpolation, approximation and compression The authors discuss real-world issues and hurdles to using these tools, and ways of adapting them to overcome problems of finiteness and localization, the limitations of uncertainty, and computational costs. It includes over 160 homework problems and over 220 worked examples, specifically designed to test and expand students' understanding of the fundamentals of signal processing, and is accompanied by extensive online materials designed to aid learning, including Mathematica® resources and interactive demonstrations.
Book Synopsis Signal Processing for Communications by : Paolo Prandoni
Download or read book Signal Processing for Communications written by Paolo Prandoni and published by Collection Savoir suisse. This book was released on 2008-06-17 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: With a novel, less classical approach to the subject, the authors have written a book with the conviction that signal processing should be taught to be fun. The treatment is therefore less focused on the mathematics and more on the conceptual aspects, the idea being to allow the readers to think about the subject at a higher conceptual level, thus building the foundations for more advanced topics. The book remains an engineering text, with the goal of helping students solve real-world problems. In this vein, the last chapter pulls together the individual topics as discussed throughout the book into an in-depth look at the development of an end-to-end communication system, namely, a modem for communicating digital information over an analog channel.
Book Synopsis Digital Signal Processing with Kernel Methods by : Jose Luis Rojo-Alvarez
Download or read book Digital Signal Processing with Kernel Methods written by Jose Luis Rojo-Alvarez and published by John Wiley & Sons. This book was released on 2018-02-05 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors: http://github.com/DSPKM • Presents the necessary basic ideas from both digital signal processing and machine learning concepts • Reviews the state-of-the-art in SVM algorithms for classification and detection problems in the context of signal processing • Surveys advances in kernel signal processing beyond SVM algorithms to present other highly relevant kernel methods for digital signal processing An excellent book for signal processing researchers and practitioners, Digital Signal Processing with Kernel Methods will also appeal to those involved in machine learning and pattern recognition.
Book Synopsis Signal Processing for Neuroscientists by : Wim van Drongelen
Download or read book Signal Processing for Neuroscientists written by Wim van Drongelen and published by Elsevier. This book was released on 2006-12-18 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the 'golden trio' in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®. - Multiple color illustrations are integrated in the text - Includes an introduction to biomedical signals, noise characteristics, and recording techniques - Basics and background for more advanced topics can be found in extensive notes and appendices - A Companion Website hosts the MATLAB scripts and several data files: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670
Book Synopsis Academic Press Library in Signal Processing by : Paulo S.R. Diniz
Download or read book Academic Press Library in Signal Processing written by Paulo S.R. Diniz and published by Academic Press. This book was released on 2013-09-21 with total page 1559 pages. Available in PDF, EPUB and Kindle. Book excerpt: This first volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in machine learning and advanced signal processing theory. With this reference source you will: - Quickly grasp a new area of research - Understand the underlying principles of a topic and its application - Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved - Quick tutorial reviews of important and emerging topics of research in machine learning - Presents core principles in signal processing theory and shows their applications - Reference content on core principles, technologies, algorithms and applications - Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge - Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic
Book Synopsis The Mathematics of Signal Processing by : Steven B. Damelin
Download or read book The Mathematics of Signal Processing written by Steven B. Damelin and published by Cambridge University Press. This book was released on 2012 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develops mathematical and probabilistic tools needed to give rigorous derivations and applications of fundamental results in signal processing theory.
Book Synopsis Image Processing for Remote Sensing by : C.H. Chen
Download or read book Image Processing for Remote Sensing written by C.H. Chen and published by CRC Press. This book was released on 2007-10-17 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edited by leaders in the field, with contributions by a panel of experts, Image Processing for Remote Sensing explores new and unconventional mathematics methods. The coverage includes the physics and mathematical algorithms of SAR images, a comprehensive treatment of MRF-based remote sensing image classification, statistical approaches for
Book Synopsis Technological Innovation for Connected Cyber Physical Spaces by : Luis M. Camarinha-Matos
Download or read book Technological Innovation for Connected Cyber Physical Spaces written by Luis M. Camarinha-Matos and published by Springer Nature. This book was released on 2023-06-24 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2023, held in Monte da Caparica, Portugal, during July 5-7, 2022. The 22 full papers presented were carefully reviewed and selected from 47 submissions. The papers cover the following topics: energy communities; smart energy and power systems; intelligent manufacturing; health and biomedical information systems; intelligent computational systems; and electronics and communications.
Author :Edited by Paul F. Kisak Publisher :Createspace Independent Publishing Platform ISBN 13 :9781523323999 Total Pages :190 pages Book Rating :4.3/5 (239 download)
Book Synopsis Hilbert Space by : Edited by Paul F. Kisak
Download or read book Hilbert Space written by Edited by Paul F. Kisak and published by Createspace Independent Publishing Platform. This book was released on 2016-01-07 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: The mathematical concept of a Hilbert space, named after David Hilbert, generalizes the notion of Euclidean space. It extends the methods of vector algebra and calculus from the two-dimensional Euclidean plane and three-dimensional space to spaces with any finite or infinite number of dimensions. A Hilbert space is an abstract vector space possessing the structure of an inner product that allows length and angle to be measured. Furthermore, Hilbert spaces are complete: there are enough limits in the space to allow the techniques of calculus to be used. Hilbert spaces arise naturally and frequently in mathematics and physics, typically as infinite-dimensional function spaces. The earliest Hilbert spaces were studied from this point of view in the first decade of the 20th century by David Hilbert, Erhard Schmidt, and Frigyes Riesz. They are indispensable tools in the theories of partial differential equations, quantum mechanics, Fourier analysis (which includes applications to signal processing and heat transfer)-and ergodic theory, which forms the mathematical underpinning of thermodynamics. John von Neumann coined the term Hilbert space for the abstract concept that underlies many of these diverse applications. The success of Hilbert space methods ushered in a very fruitful era for functional analysis. Apart from the classical Euclidean spaces, examples of Hilbert spaces include spaces of square-integrable functions, spaces of sequences, Sobolev spaces consisting of generalized functions, and Hardy spaces of holomorphic functions. This book gives a mathematical overview of the definition and use of Hilbert Space.
Book Synopsis Window Functions and Their Applications in Signal Processing by : K. M. M. Prabhu
Download or read book Window Functions and Their Applications in Signal Processing written by K. M. M. Prabhu and published by CRC Press. This book was released on 2018-09-03 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Linear Operator Theory in Engineering and Science by : Arch W. Naylor
Download or read book Linear Operator Theory in Engineering and Science written by Arch W. Naylor and published by Springer Science & Business Media. This book was released on 1982 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a unique introduction to the theory of linear operators on Hilbert space. The authors' goal is to present the basic facts of functional analysis in a form suitable for engineers, scientists, and applied mathematicians. Although the Definition-Theorem-Proof format of mathematics is used, careful attention is given to motivation of the material covered and many illustrative examples are presented. First published in 1971, Linear Operator in Engineering and Sciences has since proved to be a popular and very useful textbook.
Book Synopsis Mathematical Principles of Signal Processing by : Pierre Bremaud
Download or read book Mathematical Principles of Signal Processing written by Pierre Bremaud and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the reviews: "[...] the interested reader will find in Bremaud’s book an invaluable reference because of its coverage, scope and style, as well as of the unified treatment it offers of (signal processing oriented) Fourier and wavelet basics." Mathematical Reviews
Book Synopsis Inference and Learning from Data by : Ali H. Sayed
Download or read book Inference and Learning from Data written by Ali H. Sayed and published by Cambridge University Press. This book was released on 2022-11-30 with total page 1081 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover data-driven learning methods with the third volume of this extraordinary three-volume set.
Book Synopsis An Introduction to Hilbert Space by : N. Young
Download or read book An Introduction to Hilbert Space written by N. Young and published by Cambridge University Press. This book was released on 1988-07-21 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is an introduction to the theory of Hilbert space and its applications. The notion of Hilbert space is central in functional analysis and is used in numerous branches of pure and applied mathematics. Dr Young has stressed applications of the theory, particularly to the solution of partial differential equations in mathematical physics and to the approximation of functions in complex analysis. Some basic familiarity with real analysis, linear algebra and metric spaces is assumed, but otherwise the book is self-contained. It is based on courses given at the University of Glasgow and contains numerous examples and exercises (many with solutions). Thus it will make an excellent first course in Hilbert space theory at either undergraduate or graduate level and will also be of interest to electrical engineers and physicists, particularly those involved in control theory and filter design.
Book Synopsis Compressive Sensing of Earth Observations by : C.H. Chen
Download or read book Compressive Sensing of Earth Observations written by C.H. Chen and published by CRC Press. This book was released on 2017-05-25 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: Future remote sensing systems will make extensive use of Compressive Sensing (CS) as it becomes more integrated into the system design with increased high resolution sensor developments and the rising earth observation data generated each year. Written by leading experts in the field Compressive Sensing of Earth Observations provides a comprehensive and balanced coverage of the theory and applications of CS in all aspects of earth observations. This work covers a myriad of practical aspects such as the use of CS in detection of human vital signs in a cluttered environment and the corresponding modeling of rib-cage breathing. Readers are also presented with three different applications of CS to the ISAR imaging problem, which includes image reconstruction from compressed data, resolution enhancement, and image reconstruction from incomplete data.
Book Synopsis Data Driven Model Learning for Engineers by : Guillaume Mercère
Download or read book Data Driven Model Learning for Engineers written by Guillaume Mercère and published by Springer Nature. This book was released on 2023-08-09 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main goal of this comprehensive textbook is to cover the core techniques required to understand some of the basic and most popular model learning algorithms available for engineers, then illustrate their applicability directly with stationary time series. A multi-step approach is introduced for modeling time series which differs from the mainstream in the literature. Singular spectrum analysis of univariate time series, trend and seasonality modeling with least squares and residual analysis, and modeling with ARMA models are discussed in more detail. As applications of data-driven model learning become widespread in society, engineers need to understand its underlying principles, then the skills to develop and use the resulting data-driven model learning solutions. After reading this book, the users will have acquired the background, the knowledge and confidence to (i) read other model learning textbooks more easily, (ii) use linear algebra and statistics for data analysis and modeling, (iii) explore other fields of applications where model learning from data plays a central role. Thanks to numerous illustrations and simulations, this textbook will appeal to undergraduate and graduate students who need a first course in data-driven model learning. It will also be useful for practitioners, thanks to the introduction of easy-to-implement recipes dedicated to stationary time series model learning. Only a basic familiarity with advanced calculus, linear algebra and statistics is assumed, making the material accessible to students at the advanced undergraduate level.
