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Books > Computing & IT > Applications of computing > Signal processing
Advanced Methods in Biomedical Signal Processing and Analysis presents state-of-the-art methods in biosignal processing, including recurrence quantification analysis, heart rate variability, analysis of the RRI time-series signals, joint time-frequency analyses, wavelet transforms and wavelet packet decomposition, empirical mode decomposition, modeling of biosignals, Gabor Transform, empirical mode decomposition. The book also gives an understanding of feature extraction, feature ranking, and feature selection methods, while also demonstrating how to apply artificial intelligence and machine learning to biosignal techniques.
Power engineering has become a multidisciplinary field ranging from linear algebra, electronics, signal processing to artificial intelligence including recent trends like bio-inspired computation, lateral computing and so on. In this book, Ukil builds the bridge between these inter-disciplinary power engineering practices. The book looks into two major fields used in modern power systems: intelligent systems and the signal processing. The intelligent systems section comprises of fuzzy logic, neural network and support vector machine. The author looks at relevant theories on the topics without assuming much particular background. Following the theoretical basics, he studies their applications in various problems in power engineering, like, load forecasting, phase balancing, or disturbance analysis. These application studies are of two types: full application studies explained like in-depth case-studies, and semi-developed application ideas with scope for further extension. This is followed by pointers to further research information. In the second part, the book leads into the signal processing from the basics of the system theory, followed by fundamentals of different signal processing transforms with examples. A section follows about the sampling technique and the digital filters which are the ultimate processing tools. The theoretical basics are substantiated by some of the applications in power engineering, both in-depth and semi-developed as before. This also ends up with pointers to further research information. Intelligent Systems and Signal Processing in Power Engineering is helpful for students, researchers and engineers, trying to solve power engineering problems using intelligent systems and signal processing, or seeking applications of intelligent systems and signal processing in power engineering."
DSP Integrated Circuits establishes the essential interface between
theory of digital signal processing algorithms and their
implementation in full-custom CMOS technology. With an emphasis on
techniques for co-design of DSP algorithms and hardware in order to
achieve high performance in terms of throughput, low power
consumption, and design effort, this book provides the professional
engineer, researcher, and student with a firm foundation in the
theoretical as well as the practical aspects of designing high
performance DSP integrated circuits.
This book brings together the latest research achievements from signal processing and related disciplines, consolidating existing and proposed directions in DSP-based knowledge extraction and information fusion. The book includes contributions presenting both novel algorithms and existing applications, emphasizing on-line processing of real-world data. Readers discover applications that solve biomedical, industrial, and environmental problems.
Robust Technology with Analysis of Interference in Signal Processing discusses for the first time the theoretical fundamentals and algorithms of analysis of noise as an information carrier. On their basis the robust technology of noisy signals processing is developed. This technology can be applied to solving the problems of control, identification, diagnostics, and pattern recognition in petrochemistry, energetics, geophysics, medicine, physics, aviation, and other sciences and industries. The text explores the emergent possibility of forecasting failures on various objects, in conjunction with the fact that failures follow the hidden microchanges revealed via interference estimates. This monograph is of interest to students, postgraduates, engineers, scientific associates and others who are concerned with the processing of measuring information on computers.
This text explains how advances in wavelet analysis provide new means for multiresolution analysis and describes its wide array of powerful tools. The book covers such topics as: the variations of the windowed Fourier transform; constructions of special waveforms suitable for specific tasks; the use of redundant representations in reconstruction and enhancement; applications of efficient numerical compression as a tool for fast numerical analysis; and approximation properties of various waveforms in different contexts.
This book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed. Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal-to-noise ratio, Wiener, and tradeoff filters (including their new generalizations) can be obtained using the variable span filter framework. It then illustrates how the variable span filters can be applied in various contexts, namely in single-channel STFT-based enhancement, in multichannel enhancement in both the time and STFT domains, and, lastly, in time-domain binaural enhancement. In these contexts, the properties of these filters are analyzed in terms of their noise reduction capabilities and desired signal distortion, and the analyses are validated and further explored in simulations.
This text deals with signal processing as an important aspect of
electronic communications in its role of transmitting information,
and the language of its expression. It develops the required
mathematics in an interesting and informative way, leading to
confidence on the part of the reader. The first part of the book
focuses on continuous-time models, and contains chapters on signals
and linear systems, and on system responses. Fourier methods, so
vital in the study of information theory, are developed prior to a
discussion of methods for the design of analogue filters. The
second part of the book is directed towards discrete-time signals
and systems. There is full development of the z- and discrete
Fourier transforms to support the chapter on digital filter design.
Speech Dereverberation gathers together an overview, a mathematical formulation of the problem and the state-of-the-art solutions for dereverberation. Speech Dereverberation presents current approaches to the problem of reverberation. It provides a review of topics in room acoustics and also describes performance measures for dereverberation. The algorithms are then explained with mathematical analysis and examples that enable the reader to see the strengths and weaknesses of the various techniques, as well as giving an understanding of the questions still to be addressed. Techniques rooted in speech enhancement are included, in addition to a treatment of multichannel blind acoustic system identification and inversion. The TRINICON framework is shown in the context of dereverberation to be a generalization of the signal processing for a range of analysis and enhancement techniques. Speech Dereverberation is suitable for students at masters and doctoral level, as well as established researchers.
Praise for the Series:
Artificial Vision is a rapidly growing discipline, aiming to build
computational models of the visual functionalities in humans, as
well as machines that emulate them. Visual communication in itself
involves a numberof challenging topics with a dramatic impact on
contemporary culture where human-computer interaction and human
dialogue play a more and more significant role.
Covers advances in the field of computer techniques and algorithms in digital signal processing.
This text is the first published survey of recent research in signal processing for music transcription, edited and authored by authorities in the field. It covers a range of topics, from the structure and decomposition of signals, pitch and multipitch estimation, coding methods for sound separation, automatic sound source identification and sequence transcription, to using computational modeling and neural networks for music transcription. The book targets a growing audience interested in MPEG-7 standardization. It is a reference for researchers and students in signal processing, computer science, acoustics and music.
Advancements in digital sensor technology, digital image analysis techniques, as well as computer software and hardware have brought together the fields of computer vision and photogrammetry, which are now converging towards sharing, to a great extent, objectives and algorithms. The potential for mutual benefits by the close collaboration and interaction of these two disciplines is great, as photogrammetric know-how can be aided by the most recent image analysis developments in computer vision, while modern quantitative photogrammetric approaches can support computer vision activities. Devising methodologies for automating the extraction of man-made objects (e.g. buildings, roads) from digital aerial or satellite imagery is an application where this cooperation and mutual support is already reaping benefits. The valuable spatial information collected using these interdisciplinary techniques is of improved qualitative and quantitative accuracy. This book offers a comprehensive selection of high-quality and in-depth contributions from world-wide leading research institutions, treating theoretical as well as implementational issues, and representing the state-of-the-art on this subject among the photogrammetric and computer vision communities.
Due to the rapid increase in readily available computing power, a corre sponding increase in the complexity of problems being tackled has occurred in the field of systems as a whole. A plethora of new methods which can be used on the problems has also arisen with a constant desire to deal with more and more difficult applications. Unfortunately by increasing the ac curacy in models employed along with the use of appropriate algorithms with related features, the resultant necessary computations can often be of very high dimension. This brings with it a whole new breed of problem which has come to be known as "The Curse of Dimensionality" . The expression "Curse of Dimensionality" can be in fact traced back to Richard Bellman in the 1960's. However, it is only in the last few years that it has taken on a widespread practical significance although the term di mensionality does not have a unique precise meaning and is being used in a slightly different way in the context of algorithmic and stochastic complex ity theory or in every day engineering. In principle the dimensionality of a problem depends on three factors: on the engineering system (subject), on the concrete task to be solved and on the available resources. A system is of high dimension if it contains a lot of elements/variables and/or the rela tionship/connection between the elements/variables is complicated."
Sixth in the book series, Advances in Image Communication, which documents the rapid advancements of recent years in image communication technologies, this volume provides a comprehensive exploration of subband coding. Originally, subband coding and transform coding were developed separately. The former, however, benefitted considerably from the earlier evolution of transform coding theory and practice. Retaining their own terminology and views, the two methods are closely related and this book indeed aims to unify the approaches. Specifically, the volume contributes effectively to the understanding of frequency domain coding techniques. Many images from coding experiments are presented, enabling the reader to consider the properties of different coders. Chapter 1 introduces the problem of image compression in general terms. Sampling of images and other fundamental concepts, such as entropy and the rate distortion function, are briefly reviewed. The idea of viewing coding techniques as series expansions is also introduced. The second chapter presents signal decomposition and the conditions for perfect reconstruction from minimum representations. Chapter 3 deals with filter bank structures, primarily those displaying the perfect reconstruction property. Quantization techniques and the efficient exploitation of the bit resources are discussed from a theoretical perspective in Chapter 4 and this issue is further examined in Chapter 6, from a more practical point of view. Chapter 5 provides a development of gain formulas, i.e. quantitative measures of the performance of filter banks in a subband coding context, and these are then employed in a search for optimal filter banks. A number of examples of coded images using different subband coders are presented in Chapter 7, these indicating that subband coders give rise to some characteristic types of image degradations. Accordingly, Chapter 8 presents several techniques for minimizing these artifacts. The theory and practice of subband coding of video, at several target bit rates, is discussed in the last chapter.
Spectacular advances during the last decade have altered the
related disciplines of computing and telecommunications beyond all
recognition. The developments in the"enabling technologies,"which
have made these advances possible, have been less obvious to the
casual observer. The subject of this book is one of these
technologies--the coding of still images and picture sequences
(video).
The rapid advancements in image communication technologies are documented in the book series, Advances in Image Communication. Each publication provides an in-depth exploration of an intrinsic element of the multi-disciplinary field and together they form a comprehensive overview of the whole. This volume, the fifth in the series, examines the definition, study and use of the wavelet transform in communications for two-dimensional (2-D) digital signals. The transform is used for signal reorganization before compression and the trade-off between these two steps and the whole compression process is discussed. The five chapters specifically present the theory of wavelets applied to images, then applications of compression of still images and sequences. Chapter 1 introduces biorthogonal bases of compactly supported wavelets: this generalization of orthonormal wavelet theory allows the use of linear phase filters. A non rectangular wavelet representation of 2-D signals is developed in the second chapter: the properties usually used with wavelets, phase, linearity, and regularity are discussed. Chapter 3 is composed of three parts: a description of commonly used biorthogonal wavelets; a presentation of vector quantization algorithms; a consideration of lattice vector quantization followed by a discussion of the bit allocation procedure (with experimental results given). The fourth chapter deals with a region-based discrete wavelet transform for image coding. Chapter 5 investigates the transmission of image sequences: wavelet transforms and motion estimation are detailed in a multiconstraint approach of image sequence coding.
Image communication technologies have advanced rapidly in recent years and the book series, Advances in Image Communication is dedicated to documenting these developments. Third in the series, this publication contributes as effectively as its forerunners to the multidisciplinary overview afforded by the series as a whole. At the same time, it stands alone as a comprehensive synopsis of its own particular area of interest. The book specifically explores two complementary topics, namely: the coding algorithms made to compress the data rate of digital moving-picture sequences (video-telephony, television TV] and high-definition television HDTV]) and the transmission on Asynchronous Transfer Mode ATM] networks (packet-switching transmission media). It provides an in-depth view of the current state-of-the-art and endeavors to stimulate increasing research efforts for the future.
Signal processing applications have burgeoned in the past decade.
During the same time, signal processing techniques have matured
rapidly and now include tools from many areas of mathematics,
computer science, physics, and engineering. This trend will
continue as many new signal processing applications are opening up
in consumer products and communications systems.
This book brings together papers presented at the 2016 International Conference on Communications, Signal Processing, and Systems, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics ranging from communications to signal processing and systems, this book is aimed at undergraduate and graduate students in electrical engineering, computer science and mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD and DOE).
In the area of Digital Image Processing the new area of "Time-Varying Image Processing and Moving Oject Recognition" is contributing to impressive advances in several fields. Presented in this volume are new digital image processing and recognition methods, implementation techniques and advanced applications such as television, remote sensing, biomedicine, traffic, inspection, and robotics. New approaches (such as digital transforms, neural networks) for solving 2-D and 3-D problems are described. Many papers concentrate on motion estimation and recognition i.e. tracking of moving objects. Overall, the book describes the state-of-the-art (theory, implementation, applications) of this developing area, together with future trends. The work will be of interest not only to researchers, professors and students in university departments of engineering, communications, computers and automatic control, but also to engineers and managers of industries concerned with computer vision, manufacturing, automation, robotics and quality control.
The design and construction of three-dimensional 3-D] object recognition systems has long occupied the attention of many computer vision researchers. The variety of systems that have been developed for this task is evidence both of its strong appeal to researchers and its applicability to modern manufacturing, industrial, military, and consumer environments. 3-D object recognition is of interest to scientists and engineers in several different disciplines due to both a desire to endow computers with robust visual capabilities, and the wide applications which would benefit from mature and robust vision systems. However, 3-D object recognition is a very complex problem, and few systems have been developed for actual production use; most existing systems have been developed for experimental use by researchers only. This edited collection of papers summarizes the state of the art in 3-D object recognition using examples of existing 3-D systems developed by leading researchers in the field. While most chapters describe a complete object recognition system, chapters on biological vision, sensing, and early processing are also included. The volume will serve as a valuable reference source for readers who are involved in implementing model-based object recognition systems, stimulating the cross-fertilisation of ideas in the various domains.
The area of adaptive systems, which encompasses recursive identification, adaptive control, filtering, and signal processing, has been one of the most active areas of the past decade. Since adaptive controllers are fundamentally nonlinear controllers which are applied to nominally linear, possibly stochastic and time-varying systems, their theoretical analysis is usually very difficult. Nevertheless, over the past decade much fundamental progress has been made on some key questions concerning their stability, convergence, performance, and robustness. Moreover, adaptive controllers have been successfully employed in numerous practical applications, and have even entered the marketplace.
Multimedia Signals and Systems is an essential text for
professional and academic researchers and students in the field of
multimedia. |
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