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Books > Computing & IT > Applications of computing > Signal processing
This book proposes a combination of cognitive modeling with model-based user interface development to tackle the problem of maintaining the usability of applications that target several device types at once (e.g., desktop PC, smart phone, smart TV). Model-based applications provide interesting meta-information about the elements of the user interface (UI) that are accessible through computational introspection. Cognitive user models can capitalize on this meta-information to provide improved predictions of the interaction behavior of future human users of applications under development. In order to achieve this, cognitive processes that link UI properties to usability aspects like effectiveness (user error) and efficiency (task completion time) are established empirically, are explained through cognitive modeling, and are validated in the course of this treatise. In the case of user error, the book develops an extended model of sequential action control based on the Memory for Goals theory and it is confirmed in different behavioral domains and experimental paradigms. This new model of user cognition and behavior is implemented using the MeMo workbench and integrated with the model-based application framework MASP in order to provide automated usability predictions from early software development stages on. Finally, the validity of the resulting integrated system is confirmed by empirical data from a new application, eliciting unexpected behavioral patterns.
A Unique, Cutting-Edge Approach to Optical Filter Design With more and more information being transmitted over fiber-optic lines, optical filtering has become crucial to the advanced functionality of today’s communications networks. Helping researchers and engineers keep pace with this rapidly evolving technology, this book presents digital processing techniques for optical filter design. This higher-level approach focuses on filter characteristics and enables readers to quickly calculate the filter response as well as tackle larger and more complex filters. The authors incorporate numerous theoretical and experimental results from the literature and discuss applications to a variety of systems—including the new wavelength division multiplexing (WDM) technology, which is fast becoming the preferred method for system upgrade and expansion. Special features of this book include:
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 signal processing, communications, and controls. "Kernel Adaptive Filtering" is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, Ontario, Canada, this unique resource elevates the adaptive filtering theory to a new level, presenting a new design methodology of nonlinear adaptive filters. Covers the kernel least mean squares algorithm, kernel affine projection algorithms, the kernel recursive least squares algorithm, the theory of Gaussian process regression, and the extended kernel recursive least squares algorithm Presents a powerful model-selection method called maximum marginal likelihood Addresses the principal bottleneck of kernel adaptive filters--their growing structure Features twelve computer-oriented experiments to reinforce the concepts, with MATLAB codes downloadable from the authors' Web site Concludes each chapter with a summary of the state of the art and potential future directions for original research "Kernel Adaptive Filtering" is ideal for engineers, computer scientists, and graduate students interested in nonlinear adaptive systems for online applications (applications where the data stream arrives one sample at a time and incremental optimal solutions are desirable). It is also a useful guide for those who look for nonlinear adaptive filtering methodologies to solve practical problems.
Advanced techniques in image processing have led to many innovations supporting the medical field, especially in the area of disease diagnosis. Biomedical imaging is an essential part of early disease detection and often considered a first step in the proper management of medical pathological conditions. Classification and Clustering in Biomedical Signal Processing focuses on existing and proposed methods for medical imaging, signal processing, and analysis for the purposes of diagnosing and monitoring patient conditions. Featuring the most recent empirical research findings in the areas of signal processing for biomedical applications with an emphasis on classification and clustering techniques, this essential publication is designed for use by medical professionals, IT developers, and advanced-level graduate students.
Developed by recognized experts in the field, this first-of-its-kind resource provides an overview of the basic principles of passive radar technology, real passive radar systems and new developments in the industry. It explains in-depth how passive radar works and how it differs from the active type, while demonstrating the benefits and drawbacks of the technology. The book also explores properties of ambiguity functions, digital vs. analog, digitally-coded waveforms, vertical-plane coverage, and satellite-borne and radar illuminators. The book functions as a practical guide on direct signal suppression, passive radar performance prediction and detection and tracking. It contains concrete examples of systems and results, including analog TV, FM radio, cell phone base stations, DVB-T and DAB, HF skywave transmissions, indoor WiFi and low-cost scientific remote sensing.
This book presents works from world-class experts from academia, industry, and national agencies representing countries from across the world focused on automotive fields for in-vehicle signal processing and safety. These include cutting-edge studies on safety, driver behavior, infrastructure, and human-to-vehicle interfaces. Vehicle Systems, Driver Modeling and Safety is appropriate for researchers, engineers, and professionals working in signal processing for vehicle systems, next generation system design from driver-assisted through fully autonomous vehicles.
For those involved with the design and analysis of electro-optical systems, the book outlines current and future ground, air and spacebourne applications of electro-optical systems. It describes their performance requirements and practical methods of achieving design objectives.
This book is a collection of selected peer-reviewed papers presented at the International Conference on Signal Processing and Communication (ICSC 2018). It covers current research and developments in the fields of communications, signal processing, VLSI circuits and systems, and embedded systems. The book offers in-depth discussions and analyses of latest problems across different sub-fields of signal processing and communications. The contents of this book will prove to be useful for students, researchers, and professionals working in electronics and electrical engineering, as well as other allied fields.
Modern-day radar problems can't be solved by conventional radar technology -- but they can be solved with the ground-breaking signal processing and analysis methods presented in this unique, expertly authored book. Illustrated with nearly 400 figures and including over 70 equations.
This volume includes papers presented at IIH-MSP 2017, the 13th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, held on 12-15 August 2017 in Matsue, Shimane, Japan. The conference covered topics ranging from information hiding and security, and multimedia signal processing and networking, to bio-inspired multimedia technologies and systems. This volume focuses on subjects related to multimedia security and applications, wearable computing, Internet of Things (IoT) privacy and information security, biomedical system design and applications, emerging techniques and applications, soft computing and applications, applications of image encoding and rendering, and information hiding and its criteria. Updated with the latest research outcomes and findings, the papers presented appeal to researchers and students in the corresponding fields.
A common complaint heard in today's business office is, There is paper everywhere but I cannot find the document that I'm looking for It is estimated that 90 percent of all data and information currently being processed and distributed within offices and between organizations resides on paper. Finding the physical space to store this paper can be a key problem. To overcome this problem and others, there is a need for a dramatic new approach to information processing found in business. Such an approach is found in this unique and useful volume. Essentially, image processing systems in business use today's computer technology to solve paper processing and storage problems. Their main means of processing is performed electronically, that is, documents are captured initially on an electronic medium and forwarded to other users in the same mode. In this manner, their essential means of communicating with users is in an electronic format versus a paper one. Also, image processing systems in business are much more flexible in meeting changing user needs, especially when the data is stored on optical disk.
For courses in Probability and Random Processes. "Probability, Statistics, and Random Processes for Engineers, 4e "is a useful text for electrical and computer engineers. This book is a comprehensive treatment of probability and random processes that, more than any other available source, combines "rigor" with "accessibility." Beginning with the fundamentals of probability theory and requiring only college-level calculus, the book develops all the tools needed to understand more advanced topics such as random sequences, continuous-time random processes, and statistical signal processing. The book progresses at a leisurely pace, never assuming more knowledge than contained in the material already covered. Rigor is established by developing all results from the basic axioms and carefully defining and discussing such advanced notions as stochastic convergence, stochastic integrals and resolution of stochastic processes.
This work offers a practical, non-theoretical introduction to the principles, application and benefits of multi-sensor technology in smart weapon development, surveillance systems, and an increasing variety of non-military applications. It also provides an overview of MMW (Millimeter-Wave) and IR (infrared) sensor constraints, design principles, system alternatives and targeting applications.
This book gives a concise introduction to both image and video processing, providing a balanced coverage between theory, applications and standards. It gives an introduction to both 2-D and 3-D signal processing theory, supported by an introduction to random processes and some essential results from information theory, providing the necessary foundation for a full understanding of the image and video processing concepts that follow. A significant new feature is the explanation of practical network coding methods for image and video transmission. There is also coverage of new approaches such as: super-resolution methods, non-local processing, and directional transforms. This book also has on-line support that contains many short MATLAB programs that complement examples and exercises on multidimensional signal, image, and video processing. There are numerous short video clips showing applications in video processing and coding, plus a copy of the vidview video player for playing .yuv video files on a Windows PC and an illustration of the effect of packet loss on H.264/AVC coded bitstreams. New to this edition: New appendices on random processes, information theory New coverage of image analysis - edge detection, linking, clustering, and segmentation Expanded coverage on image sensing and perception, including color spaces. Now summarizes the new MPEG coding standards: scalable video coding (SVC) and multiview video coding (MVC), in addition to coverage of H.264/AVC. Updated video processing material including new example on scalable video coding and more material on object- and region-based video coding. More on video coding for networks including practical network coding (PNC), highlighting the significant advantages of PNC for both video downloading and streaming. New coverage of super-resolution methods for image and
video.
The main objective of this book is to provide a multidisciplinary overview of methodological approaches, architectures, platforms, and algorithms for the realization of an Internet of Things (IoT)-based Smart Urban Ecosystem (SUE). Moreover, the book details a set of real-world applications and case studies related to specific smart infrastructures and smart cities, including structural health monitoring, smart urban drainage networks, smart grids, power efficiency, healthcare, city security, and emergency management. A Smart Urban Ecosystem (SUE) is a people-centric system of systems that involves smart city environments, applications, and infrastructures. SUEs require the close integration of cyber and physical components for monitoring, understanding and controlling the urban environment. In this context, the Internet of Things (IoT) offers a valuable enabling technology, as it bridges the gap between physical things and software components, and empowers cooperation between distributed, pervasive, and heterogeneous entities.
There have been significant developments in the design and application of algorithms for both one-dimensional signal processing and multidimensional signal processing, namely image and video processing, with the recent focus changing from a step-by-step procedure of designing the algorithm first and following up with in-depth analysis and performance improvement to instead applying heuristic-based methods to solve signal-processing problems. In this book the contributing authors demonstrate both general-purpose algorithms and those aimed at solving specialized application problems, with a special emphasis on heuristic iterative optimization methods employing modern evolutionary and swarm intelligence based techniques. The applications considered are in domains such as communications engineering, estimation and tracking, digital filter design, wireless sensor networks, bioelectric signal classification, image denoising, and image feature tracking. The book presents interesting, state-of-the-art methodologies for solving real-world problems and it is a suitable reference for researchers and engineers in the areas of heuristics and signal processing."
In three parts, this book contributes to the advancement of engineering education and that serves as a general reference on digital signal processing. Part I presents the basics of analog and digital signals and systems in the time and frequency domain. It covers the core topics: convolution, transforms, filters, and random signal analysis. It also treats important applications including signal detection in noise, radar range estimation for airborne targets, binary communication systems, channel estimation, banking and financial applications, and audio effects production. Part II considers selected signal processing systems and techniques. Core topics covered are the Hilbert transformer, binary signal transmission, phase-locked loops, sigma-delta modulation, noise shaping, quantization, adaptive filters, and non-stationary signal analysis. Part III presents some selected advanced DSP topics.
This is a uniquely comprehensive reference that summarizes the
state of the art of signal processing theory and techniques for
solving emerging problems in neuroscience, and which clearly
presents new theory, algorithms, software and hardware tools that
are specifically tailored to the nature of the neurobiological
environment. It gives a broad overview of the basic principles,
theories and methods in statistical signal processing for basic and
applied neuroscience problems.
Low-power sensors and their applications in various fields ranging from military to civilian lives have made tremendous progress in the recent years. Low-power and extended battery life are the key focuses for long term, reliable and easy operation of these sensors. Sensors and Low Power Signal Processing provides a general overview of a sensor's working principle and a discussion of the emerging sensor technologies including chemical, electro-chemical and MEMS based sensors. Also included is a discussion on design challenges associated with low-power analog circuits and the schemes to overcome them. Finally, a short discussion of some of the simple wireless telemetry schemes best suited for low-power sensor applications and sensor packaging issues is discussed. Applications and sensor prototypes included are environmental monitoring, health care monitoring and issues related to the development of sensor prototypes and associated electronics to achieve high signal-to-noise ratio will also be presented.
This reference provides an in-depth discussion of the theory and application of lapped transforms (LTs). It explains how LTs can lead to a better complexity/performance trade-off than other transforms or filter bands used in signal processing. The text addresses the increased use LTs, especially with HDTV and how they may become the standard for high-quality audio coding.
DSP is utilized in just about every electronic system or device. DSP is taking one piece of information be it data, image, video, or audio, most likely compressing, sending, and filtering it to another location within your application to appear in the form of a document, picture or video. Like Smith before it, this book is different to most on the market by following a popular applied approach to this tricky subject, and will be the perfect starting point for engineers who need to get into DSP from the ground floor. This book starts with the absolute basics of this integral process. No experience is expected and with no prior knowledge taken for
granted, a refresher chapter on complex numbers and trigonometry
can be found at the very beginning of the material. Real-world
worked examples, reference designs, and tools - including online
applets that enable readers to visualize key principles - complete
a package that will help engineers who that needs to learn anew or
refresh their memory on this essential technology as they move to
projects that require DSP familiarity. Clear examples and a non-mathematical approach gets you up to speed with DSP Includes an overview of the DSP functions and implementation used in typical DSP-intensive applications, including error correction, CDMA mobile communication, and radar systems
The latest research and developments in robust adaptive beamforming
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