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Books > Computing & IT > Applications of computing > Signal processing
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.
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).
Audio and speech processing have achieved important status in development in the last three decades, improving the standard of living of many people. Regarding these applications, several signal processing algorithms have been developed to assist the speech impaired and improve the learning ability of children. Advances in Audio and Speech Signal Processing: Technologies and Applications provides a comprehensive approach of signal processing tools regarding the enhancement, recognition, and protection of speech and audio signals. Advances in Audio and Speech Signal Processing: Technologies and Applications offers researchers and practitioners the information they need to develop and implement efficient signal processing algorithms in the enhancement field.
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.
A smart camera is an integrated machine vision system which, in addition to image capture circuitry, includes a processor, which can extract information from images without need for an external processing unit, and interface devices used to make results available to other devices. This book provides content on smart cameras for an interdisciplinary audience of professionals and students in embedded systems, image processing, and camera technology. It serves as a self-contained, single-source reference for material otherwise found only in sources such as conference proceedings, journal articles, or product data sheets. Coverage includes the 50 year chronology of smart cameras, their technical evolution, the state-of-the art, and numerous applications, such as surveillance and monitoring, robotics, and transportation.
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.
The book presents basic and advanced concepts of circularly polarized antennas, including design procedure and recent applications. Cross dipole antennas, microstrip antennas, helical antennas, quadrifilar helix antennas, frequency independent antennas, horn antennas, omnidirectional circularly polarized antennas and radial line arry antennas are discussed. With abundant examples, the book is an essential reference for researchers and engineers.
This book presents models and procedures to design pipeline analog-to-digital converters, compensating for device inaccuracies, so that high-performance specs can be met within short design cycles. These models are capable of capturing and predicting the behavior of pipeline data converters within less than half-a-bit deviation, versus transistor-level simulations. As a result, far fewer model iterations are required across the design cycle. Models described in this book accurately predict transient behaviors, which are key to the performance of discrete-time systems and hence to the performance of pipeline data converters.
Signal Measurement and Estimation Techniques for Micro and
Nanotechnology discusses micro, nano and robotic cells and gives a
state-of-the-art presentation of the different techniques and
solutions to measure and estimate signals at the micro and nano
scale. New technologies and applications such as micromanipulation
(artificial components, biological objects), micro-assembly (MEMS,
MOEMS, NEMS) and material and surface force characterization are
covered. The importance of sensing at the micro and nano scale is
presented as a key issue in control systems, as well as for
understanding the physical phenomena of these systems. The book
also:
Essential background reading for engineers and scientists working in such fields as communications, control, signal, and image processing, radar and sonar, radio astronomy, seismology, remote sensing, and instrumentation. The book can be used as a textbook for a single course, as well as a combination of an introductory and an advanced course, or even for two separate courses, one in signal detection, the other in estimation.
Learn how and when to apply the latest phase and phase-difference modulation (PDM) techniques with this valuable guide for systems engineers and researchers. It helps you cut design time and fine-tune system performance.
A key element of any modern video codec is the efficient exploitation of temporal redundancy via motion-compensated prediction. In this book, a novel paradigm of representing and employing motion information in a video compression system is described that has several advantages over existing approaches. Traditionally, motion is estimated, modelled, and coded as a vector field at the target frame it predicts. While this "prediction-centric" approach is convenient, the fact that the motion is "attached" to a specific target frame implies that it cannot easily be re-purposed to predict or synthesize other frames, which severely hampers temporal scalability. In light of this, the present book explores the possibility of anchoring motion at reference frames instead. Key to the success of the proposed "reference-based" anchoring schemes is high quality motion inference, which is enabled by the use of a more "physical" motion representation than the traditionally employed "block" motion fields. The resulting compression system can support computationally efficient, high-quality temporal motion inference, which requires half as many coded motion fields as conventional codecs. Furthermore, "features" beyond compressibility - including high scalability, accessibility, and "intrinsic" framerate upsampling - can be seamlessly supported. These features are becoming ever more relevant as the way video is consumed continues shifting from the traditional broadcast scenario to interactive browsing of video content over heterogeneous networks. This book is of interest to researchers and professionals working in multimedia signal processing, in particular those who are interested in next-generation video compression. Two comprehensive background chapters on scalable video compression and temporal frame interpolation make the book accessible for students and newcomers to the field.
The fields of image analysis, computer vision, and artificial intelligence all make use of descriptions of shape in grey-level images. Most existing algorithms for the automatic recognition and classification of particular shapes have been devel oped for specific purposes, with the result that these methods are often restricted in their application. The use of advanced and theoretically well-founded math ematical methods should lead to the construction of robust shape descriptors having more general application. Shape description can be regarded as a meeting point of vision research, mathematics, computing science, and the application fields of image analy sis, computer vision, and artificial intelligence. The NATO Advanced Research Workshop "Shape in Picture" was organised with a twofold objective: first, it should provide all participants with an overview of relevant developments in these different disciplines; second, it should stimulate researchers to exchange original results and ideas across the boundaries of these disciplines. This book comprises a widely drawn selection of papers presented at the workshop, and many contributions have been revised to reflect further progress in the field. The focus of this collection is on mathematical approaches to the construction of shape descriptions from grey-level images. The book is divided into five parts, each devoted to a different discipline. Each part contains papers that have tutorial sections; these are intended to assist the reader in becoming acquainted with the variety of approaches to the problem."
Foundations of Digital Signal Processing: Theory, algorithms and hardware design starts by introducing the mathematical foundations of DSP, assuming little prior knowledge of the subject from the reader, and moves on to discuss more complex topics such as Fourier, Laplace and digital filtering. It provides detailed information on off-line, real-time and DSP programming, and guides the reader through advanced topics such as DSP hardware design, FIR and IIR filter design and difference equation manipulation. A CD accompanies the book. It provides the reader with programs that demonstrate equations discussed in the text and source codes to enable the reader to incorporate algorithms into their own DSP programs.
This graduate-level text lays out the foundation of DSP for audio and the fundamentals of auditory perception, then goes on to discuss immersive audio rendering and synthesis, the digital equalization of room acoustics, and various DSP implementations. It covers a variety of topics and up-to-date results in immersive audio processing research: immersive audio synthesis and rendering, multichannel room equalization, audio selective signal cancellation, multirate signal processing for audio applications, surround sound processing, psychoacoustics and its incorporation in audio signal processing algorithms for solving various problems, and DSP implementations of audio processing algorithms on semiconductor devices.
A valuable resource for radar engineers and managers of all levels, this revised edition provides an introduction to the capabilities and limitations of radar, as well as a detailed advanced study of key radar signal processing topics. The book explains the concepts and theory of radar signal processing such as resolution, ambiguities, antennas, waveforms, the theory of detecting targets in noise and/or clutter, and tracking using data processing. It also presents equations for the determination of maximum radar range in free space and as affected by multipath and the horizon.
A resource like no other—the first comprehensive guide to phase unwrapping Phase unwrapping is a mathematical problem-solving technique increasingly used in synthetic aperture radar (SAR) interferometry, optical interferometry, adaptive optics, and medical imaging. In Two-Dimensional Phase Unwrapping, two internationally recognized experts sort through the multitude of ideas and algorithms cluttering current research, explain clearly how to solve phase unwrapping problems, and provide practicable algorithms that can be applied to problems encountered in diverse disciplines. Complete with case studies and examples as well as hundreds of images and figures illustrating the concepts, this book features:
Two-Dimensional Phase Unwrapping skillfully integrates concepts, algorithms, software, and examples into a powerful benchmark against which new ideas and algorithms for phase unwrapping can be tested. This unique introduction to a dynamic, rapidly evolving field is essential for professionals and graduate students in SAR interferometry, optical interferometry, adaptive optics, and magnetic resonance imaging (MRI).
Optimization of adaptive signal processing algorithms for wireless communications is based on a model of the underlying propagation channel. In practice, this model is never known perfectly. For example, its parameters have to be estimated and are only known with significant errors. In this book, a systematic treatment of this practical design problem is provided for signal processing in the physical layer with multiple antennas. The design of robust signal processing algorithms is based on a description of the errors and the uncertainties in the system's model. It applies principles of modern estimation, optimization, and information theory. Tutorial introductions to relevant literature and mathematical foundations give the necessary background and context to the reader. The book provides detailed derivations and enlightening insights into the related technical problems covering the following topics in detail: An overview of the principles of training-based multiple-input multiple-output (MIMO) channel estimation. Robust minimax estimation of the wireless communication channel. Robust minimax prediction of the wireless communication channel based on the maximum Doppler frequency. Identification of channel and noise correlations (power delay profile, spatial and temporal correlations, spatial correlations of interference). Interpolation of band-limited autocovariance sequences. Robust linear and nonlinear precoding for the multi-user downlink with multiple antennas which is based on incomplete channel state information or channel correlations (performance measures, duality, robust Tomlinson-Harashima precoding, robust vector precoding, nonlinear beamforming).
This book provides various speech enhancement algorithms for digital hearing aids. It covers information on noise signals extracted from silences of speech signal. The description of the algorithm used for this purpose is also provided. Different types of adaptive filters such as Least Mean Squares (LMS), Normalized LMS (NLMS) and Recursive Lease Squares (RLS) are described for noise reduction in the speech signals. Different types of noises are taken to generate noisy speech signals, and therefore information on various noises signals is provided. The comparative performance of various adaptive filters for noise reduction in speech signals is also described. In addition, the book provides a speech enhancement technique using adaptive filtering and necessary frequency strength enhancement using wavelet transform as per the requirement of audiogram for digital hearing aids. Presents speech enhancement techniques for improving performance of digital hearing aids; Covers various types of adaptive filters and their advantages and limitations; Provides a hybrid speech enhancement technique using wavelet transform and adaptive filters.
This book addresses the challenges and design trade-offs arising during the hardware design of Faster-than-Nyquist (FTN) signaling transceivers. The authors describe how to design for coexistence between the FTN system described and Orthogonal frequency-division multiplexing (OFDM) systems, enabling readers to design FTN specific processing blocks as add-ons to the conventional transceiver chain. Provides a comprehensive introduction to Faster-than-Nyquist
(FTN) signaling transceivers, covering both theory and hardware
implementation;
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.
This graduate-level text provides a language for understanding, unifying, and implementing a wide variety of algorithms for digital signal processing - in particular, to provide rules and procedures that can simplify or even automate the task of writing code for the newest parallel and vector machines. It thus bridges the gap between digital signal processing algorithms and their implementation on a variety of computing platforms. The mathematical concept of tensor product is a recurring theme throughout the book, since these formulations highlight the data flow, which is especially important on supercomputers. Because of their importance in many applications, much of the discussion centres on algorithms related to the finite Fourier transform and to multiplicative FFT algorithms.
129 6.2 Representation of hints. 131 6.3 Monotonicity hints .. . 134 6.4 Theory ......... . 139 6.4.1 Capacity results 140 6.4.2 Decision boundaries 144 6.5 Conclusion 145 6.6 References....... ... 146 7 Analysis and Synthesis Tools for Robust SPRness 147 C. Mosquera, J.R. Hernandez, F. Perez-Gonzalez 7.1 Introduction.............. 147 7.2 SPR Analysis of Uncertain Systems. 153 7.2.1 The Poly topic Case . 155 7.2.2 The ZP-Ball Case ...... . 157 7.2.3 The Roots Space Case ... . 159 7.3 Synthesis of LTI Filters for Robust SPR Problems 161 7.3.1 Algebraic Design for Two Plants ..... . 161 7.3.2 Algebraic Design for Three or More Plants 164 7.3.3 Approximate Design Methods. 165 7.4 Experimental results 167 7.5 Conclusions 168 7.6 References ..... . 169 8 Boundary Methods for Distribution Analysis 173 J.L. Sancho et aZ. 8.1 Introduction ............. . 173 8.1.1 Building a Classifier System . 175 8.2 Motivation ............. . 176 8.3 Boundary Methods as Feature-Set Evaluation 177 8.3.1 Results ................ . 179 8.3.2 Feature Set Evaluation using Boundary Methods: S- mary. . . . . . . . . . . . . . . . . . . .. . . 182 . . . |
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