Digital Signal Processing and Parallel Algorithms

Online learning from a signal processing perspective There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced sign

A comprehensive, tutorial-style introduction to the algorithms for reconstructing cross-sectional images from projection data and contains a complete overview of the engineering and signal processing

French physicists and engineers survey new designs for antennas that respond to new materials and technologies, new algorithms and increased speed for signal processing, and new requirements and appli

In the fourth edition of Adaptive Filtering: Algorithms and Practical Implementation, author Paulo S.R. Diniz presents the basic concepts of adaptive signal processing and adaptive filtering in a conc

Due to parallel advances in signal processing and computer hardware in the last 15 years, quantitative ultrasound techniques have reached maturity, allowing for the construction of quantitative maps o

Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia

This graduate-level text augments and extends studies of signal processing, particularly in regard to communication systems and digital filtering theory. Topics include filtering, linear systems, and

A comprehensive text and reference that covers all aspects of computer music, including digital audio, synthesis techniques, signal processing, musical input devices, performance software, editing sy

強力推薦：Digital Signal Processing Using Matlab 英文原版火熱發售

This is the first comprehensive book on arithmetic circuits for digital signal processing (DSP) to provide key concepts, developments, and applications for different types of arithmetic circuits,

For introductory courses (sophomore/junior) in Digital Signal Processing and Signals and Systems. Text is useful as a self-teaching tool for anyone eager to discover more about DSP applications, multi

This book discusses the trade-offs involved in designing direct RF digitization receivers for the radio frequency and digital signal processing domains. A system-level framework is developed, quantif

Communication Acoustics deals with the fundamentals of those areas of acoustics which are related to modern communication technologies. Due to the advent of digital signal processing and recording in

Based on the authors’ research in Fourier analysis, Brief Notes in Advanced DSP: Fourier Analysis with MATLABR addresses many concepts and applications of digital signal processing (DSP). The included

This book was first published in 2004. In many applications, images, such as ultrasonic or X-ray signals, are recorded and then analyzed with digital or optical processors in order to extract information. Such processing requires the development of algorithms of great precision and sophistication. This book presents a unified treatment of the mathematical methods that underpin the various algorithms used in remote image formation. The author begins with a review of transform and filter theory. He then discusses two- and three-dimensional Fourier transform theory, the ambiguity function, image construction and reconstruction, tomography, baseband surveillance systems, and passive systems (where the signal source might be an earthquake or a galaxy). Information-theoretic methods in image formation are also covered, as are phase errors and phase noise. Throughout the book, practical applications illustrate theoretical concepts, and there are many homework problems. The book is aimed at gr

This book was first published in 2004. In many applications, images, such as ultrasonic or X-ray signals, are recorded and then analyzed with digital or optical processors in order to extract information. Such processing requires the development of algorithms of great precision and sophistication. This book presents a unified treatment of the mathematical methods that underpin the various algorithms used in remote image formation. The author begins with a review of transform and filter theory. He then discusses two- and three-dimensional Fourier transform theory, the ambiguity function, image construction and reconstruction, tomography, baseband surveillance systems, and passive systems (where the signal source might be an earthquake or a galaxy). Information-theoretic methods in image formation are also covered, as are phase errors and phase noise. Throughout the book, practical applications illustrate theoretical concepts, and there are many homework problems. The book is aimed at gr

Iterative processing is an important technique with numerous applications. Exploiting the power of factor graphs, this detailed survey provides a general framework for systematically developing iterative algorithms for digital receivers, and highlights connections between important algorithms. Starting with basic concepts in digital communications, progressively more complex ideas are presented and integrated resulting in the development of cutting-edge algorithms for iterative receivers. Real-world applications are covered in detail, including decoding for turbo and LDPC codes, and detection for multi-antenna and multi-user systems. This accessible framework will allow the reader to apply factor graphs to practical problems, leading to the design of new algorithms in applications beyond digital receivers. With many examples and algorithms in pseudo-code, this book is an invaluable resource for graduate students and researchers in electrical engineering and computer science, and for pr

Because of the wide use of adaptive filtering in digital signal processing and, because most of the modern electronic devices include some type of an adaptive filter, a text that brings forth the fund

Image registration employs digital image processing in order to bring two or more digital images into precise alignment for analysis and comparison. Accurate registration algorithms are essential for creating mosaics of satellite images and tracking changes on the planet's surface over time. Bringing together invited contributions from thirty-six distinguished researchers, the book presents a detailed overview of current research and practice in the application of image registration to remote sensing imagery. Chapters cover the problem definition, theoretical issues in accuracy and efficiency, fundamental algorithms, and real-world case studies of image registration software applied to imagery from operational satellite systems. This book provides a comprehensive and practical overview for Earth and space scientists, presents image processing researchers with a summary of current research, and can be used for specialised graduate courses.

Providing a novel approach to sparsity, this comprehensive book presents the theory of stochastic processes that are ruled by linear stochastic differential equations, and that admit a parsimonious representation in a matched wavelet-like basis. Two key themes are the statistical property of infinite divisibility, which leads to two distinct types of behaviour - Gaussian and sparse - and the structural link between linear stochastic processes and spline functions, which is exploited to simplify the mathematical analysis. The core of the book is devoted to investigating sparse processes, including a complete description of their transform-domain statistics. The final part develops practical signal-processing algorithms that are based on these models, with special emphasis on biomedical image reconstruction. This is an ideal reference for graduate students and researchers with an interest in signal/image processing, compressed sensing, approximation theory, machine learning, or statistic

In this complete introduction to the theory of finding derivatives of scalar-, vector- and matrix-valued functions with respect to complex matrix variables, Hjørungnes describes an essential set of mathematical tools for solving research problems where unknown parameters are contained in complex-valued matrices. The first book examining complex-valued matrix derivatives from an engineering perspective, it uses numerous practical examples from signal processing and communications to demonstrate how these tools can be used to analyze and optimize the performance of engineering systems. Covering un-patterned and certain patterned matrices, this self-contained and easy-to-follow reference deals with applications in a range of areas including wireless communications, control theory, adaptive filtering, resource management and digital signal processing. Over 80 end-of-chapter exercises are provided, with a complete solutions manual available online.

Increase the efficient use of time-varying available spectrum with this unique book, the first to describe RF hardware design for white space applications, including both analog and digital approaches. Emerging technologies are discussed and signal processing issues are addressed, providing the background knowledge and practical tools needed to develop future radio technologies. Real-world examples are included, together with global spectrum regulations and policies, for a practical approach to developing technologies for worldwide applications. Cross analog and digital design guidelines are provided to help cut design time and cost. This holistic, system level view of transceiver design for white space technologies is ideal for practising engineers and students and researchers in academia.

dimensional signal sampling problem, which has attracted a lot of research interest and become a convergence point between computer graphics and signal processing, and even computer vision. This le

Large MIMO systems, with tens to hundreds of antennas, are a promising emerging communication technology. This book provides a unique overview of this technology, covering the opportunities, engineering challenges, solutions and state of the art of large MIMO test beds. There is in-depth coverage of algorithms for large MIMO signal processing, based on meta-heuristics, belief propagation and Monte Carlo sampling techniques, and suited for large MIMO signal detection, precoding and LDPC code designs. The book also covers the training requirement and channel estimation approaches in large-scale point-to-point and multi-user MIMO systems; spatial modulation is also included. Issues like pilot contamination and base station cooperation in multi-cell operation are addressed. A detailed exposition of MIMO channel models, large MIMO channel sounding measurements in the past and present, and large MIMO test beds is also presented. An ideal resource for academic researchers, next generation wir

This book provides a comprehensive overview of the fundamental principles and applications of semiconductor diode laser arrays. All of the major types of arrays are discussed in detail, including coherent, incoherent, edge- and surface-emitting, horizontal- and vertical-cavity, individually addressed, lattice-matched and strained-layer systems. The initial chapters cover such topics as lasers, amplifiers, external-cavity control, theoretical modelling, and operational dynamics. Spatially incoherent arrays are then described in detail, and the uses of vertical-cavity surface emitter and edge-emitting arrays in parallel optical-signal processing and multi-channel optical recording are discussed. Engineers, established researchers and graduate students studying the properties and applications of such arrays will find this book invaluable.

This book presents advances in matrix and tensor data processing in the domain of signal, image and information processing. The theoretical mathematical approaches are discusses in the context of pote

This book presents advances in matrix and tensor data processing in the domain of signal, image and information processing. The theoretical mathematical approaches are discusses in the context of pote

Despite the interest in parallelism and parallel processing, there is a fundamental question that has remained largely unexplored, namely the question of how to design multiprograms (parallel programs

This first book on greedy approximation gives a systematic presentation of the fundamental results. It also contains an introduction to two hot topics in numerical mathematics: learning theory and compressed sensing. Nonlinear approximation is becoming increasingly important, especially since two types are frequently employed in applications: adaptive methods are used in PDE solvers, while m-term approximation is used in image/signal/data processing, as well as in the design of neural networks. The fundamental question of nonlinear approximation is how to devise good constructive methods (algorithms) and recent results have established that greedy type algorithms may be the solution. The author has drawn on his own teaching experience to write a book ideally suited to graduate courses. The reader does not require a broad background to understand the material. Important open problems are included to give students and professionals alike ideas for further research.

This book presents a comprehensive, systematic approach to the development of vision system architectures that employ sensory-processing concurrency and parallel processing to meet the autonomy challe

A Signal Processing Approach. An introductory text for upper level students, and also researchers and professionals.

This accessible yet in-depth textbook describes the step-by-step processes involved in biomedical device design. Integrating microfabrication techniques, sensors and digital signal processing with key clinical applications, it covers: the measurement, amplification and digitization of physiological signals, and the removal of interfering signals; the transmission of signals from implanted sensors through the body, and the issues surrounding the powering of these sensors; networks for transferring sensitive patient data to hospitals for continuous home-monitoring systems; tests for ensuring patient safety; the cost-benefit and technological trade-offs involved in device design; and current challenges in biomedical device design. With dedicated chapters on electrocardiography, digital hearing aids and mobile health, and including numerous end-of-chapter homework problems, online solutions and additional references for extended learning, it is the ideal resource for senior undergraduate s

Mahler describes random set information fusion for signal processing for graduate students, researchers, and engineers and for mathematicians and statisticians interested in tracking, information fusi

This self-contained introduction to machine learning, designed from the start with engineers in mind, will equip students with everything they need to start applying machine learning principles and algorithms to real-world engineering problems. With a consistent emphasis on the connections between estimation, detection, information theory, and optimization, it includes: an accessible overview of the relationships between machine learning and signal processing, providing a solid foundation for further study; clear explanations of the differences between state-of-the-art techniques and more classical methods, equipping students with all the understanding they need to make informed technique choices; demonstration of the links between information-theoretical concepts and their practical engineering relevance; reproducible examples using Matlab, enabling hands-on student experimentation. Assuming only a basic understanding of probability and linear algebra, and accompanied by lecture slide

This book is devoted to optical semiconductor devices and their numerous applications in telecommunications, optoelectronics, and consumer electronics-areas where signal processing or the transmission

What is the mind? How does it work? How does it influence behavior? Some psychologists hope to answer such questions in terms of concepts drawn from computer science and artificial intelligence. They test their theories by modeling mental processes in computers. This book shows how computer models are used to study many psychological phenomena - including vision, language, reasoning, and learning. It also shows that computer modeling involves differing theoretical approaches. Computational psychologists disagree about some basic questions. For instance, should the mind be modeled by digital computers, or by parallel-processing systems more like brains? Do computer programs consist of meaningless patterns, or do they embody (and explain) genuine meaning?

This comprehensive handbook of mathematical and programming techniques for audio signal processing will be an essential reference for all computer musicians, computer scientists, engineers, and anyon

Benefiting from both time-domain and frequency-domain signal processing techniques, multicarrier systems have the potential for achieving high spectral-efficiency, high-flexibility and low-complexity

This book will describe ultra low-power, integrated circuits and systems designed for the emerging field of neural signal recording and processing, and wireless communication. Since neural interfaces

Spoken language understanding (SLU) is an emerging field in between speech and language processing, investigating human/ machine and human/ human communication by leveraging technologies from signal p