Cooperative and Graph Signal Processing: Principles and Applications presents the fundamentals of signal processing over networks and the latest advances in graph signal processing. A range of key concepts are clearly explained, including learning, adaptation, optimization, control, inference and machine learning. Building on the principles of these areas, the book then shows how they are relevant to understanding distributed communication, networking and sensing and social networks. Finally, the book shows how the principles are applied to a range of applications, such as Big data, Media and video, Smart grids, Internet of Things, Wireless health and Neuroscience. With this book readers will learn the basics of adaptation and learning in networks, the essentials of detection, estimation and filtering, Bayesian inference in networks, optimization and control, machine learning, signal processing on graphs, signal processing for distributed communication, social networks from the perspective of flow of information, and how to apply signal processing methods in distributed settings.

Discover a modern approach to the analysis, modeling and design of high sensitivity phased arrays. Network theory, numerical methods and computational electromagnetic simulation techniques are uniquely combined to enable full system analysis and design optimization. Beamforming and array signal processing theory are integrated into the treatment from the start. Digital signal processing methods such as polyphase filtering and RFI mitigation are described, along with technologies for real-time hardware implementation. Key concepts from interferometric imaging used in radio telescopes are also considered. A basic development of theory and modeling techniques is accompanied by problem sets that guide readers in developing modeling codes that retain the simplicity of the classical array factor method while incorporating mutual coupling effects and interactions between elements. Combining current research trends with pedagogical material suitable for a first-year graduate course, this is an invaluable resource for students, teachers, researchers, and practicing RF/microwave and antenna design engineers.

Nowadays, many aspects of electrical and electronic engineering are essentially applications of DSP. This is due to the focus on processing information in the form of digital signals, using certain DSP hardware designed to execute software. Fundamental topics in digital signal processing are introduced with theory, analytical tables, and applications with simulation tools. The book provides a collection of solved problems on digital signal processing and statistical signal processing. The solutions are based directly on the math-formulas given in extensive tables throughout the book, so the reader can solve practical problems on signal processing quickly and efficiently. FEATURES Explains how applications of DSP can be implemented in certain programming environments designed for real time systems, ex. biomedical signal analysis and medical image processing. Pairs theory with basic concepts and supporting analytical tables. Includes an extensive collection of solved problems throughout the text. Fosters the ability to solve practical problems on signal processing without focusing on extended theory. Covers the modeling process and addresses broader fundamental issues.

The Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces: user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This second volume of the handbook begins with multimodal signal processing, architectures, and machine learning. It includes recent deep learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. These chapters discuss real-time multimodal analysis of emotion and social signals from various modalities, and perception of affective expression by users. Further chapters discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this rapidly expanding field. In the final section of this volume, experts exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade.

The Handbook of Multimodal-Multisensor Interfaces provides the first authoritative resource on what has become the dominant paradigm for new computer interfaces: user input involving new media (speech, multi-touch, hand and body gestures, facial expressions, writing) embedded in multimodal-multisensor interfaces that often include biosignals. This edited collection is written by international experts and pioneers in the field. It provides a textbook, reference, and technology roadmap for professionals working in this and related areas. This second volume of the handbook begins with multimodal signal processing, architectures, and machine learning. It includes recent deep learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. These chapters discuss real-time multimodal analysis of emotion and social signals from various modalities, and perception of affective expression by users. Further chapters discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology and tutorial support for mastering this rapidly expanding field. In the final section of this volume, experts exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade.

This book is about recent research in the area of profiling humans from their voice, which seeks to deduce and describe the speaker's entire persona and their surroundings from voice alone. It covers several key aspects of this technology, describing how the human voice is unique in its ability to both capture and influence the human persona -- how, in some ways, voice is more potent and valuable then DNA and fingerprints as a metric, since it not only carries information about the speaker, but also about their current state and their surroundings at the time of speaking. It provides a comprehensive review of advances made in multiple scientific fields that now contribute to its foundations. It describes how artificial intelligence enables mechanisms of discovery that were not possible before in this context, driving the field forward in unprecedented ways. It also touches upon related and relevant challenges posed by voice disguise and other mechanisms of voice manipulation. The book acts as a good resource for academic researchers, and for professional agencies in many areas such as law enforcement, healthcare, social services, entertainment etc.

This book collects a number of papers presented at the International Conference on Sensing and Imaging, which was held at Chengdu University of Information Technology on June 5-7, 2017. Sensing and imaging is an interdisciplinary field covering a variety of sciences and techniques such as optics, electricity, magnetism, heat, sound, mathematics, and computing technology. The field has diverse applications of interest such as sensing techniques, imaging, and image processing techniques. This book will appeal to professionals and researchers within the field.

This book introduces the basic concepts of signal processing for scientists and students with no engineering background. The book presents the concepts with minimum use of mathematical formulations and more emphasis on visual illustrations. The idea is to present an intuitive approach to understanding the basics of signal processing and exemplify some practical applications of the concepts by which the readers achieve basic knowledge and skills in signal processing. Most of illustrations in the book have been created by computer programming in MATLAB (R); thus, the reader will learn the basics of using computers in signal processing applications.

Massive multiple-input multiple-output (Massive MIMO) is the latest technology that will improve the speed and throughput of wireless communication systems for years to come. Whilst there may be some debate over the origins of the term Massive MIMO and what it precisely means, this monograph describes in detail how the research conducted in the past decades lead to a scalable multiantenna technology that offers great throughput and energy efficiency under practical conditions. Written for students, practicing engineers and researchers who want to learn the conceptual and analytical foundations of Massive MIMO, in terms of spectral, energy, and/or hardware efficiency, as well as channel estimation and practical considerations, it provides a clear and tutorial like exposition of all the major topics. It also connects the dots of the research literature covering numerous topics not easily found therein. Massive MIMO Networks is the first monograph on the subject to cover the spatial channel correlation and consider rigorous signal processing design essential for the complete understanding by its target audience.

This textbook is unique because of its in-depth treatment of the applications of wavelets and wavelet transforms to many areas, across many disciplines. The book is written to serve the needs of a one or two semester course at either the undergraduate or graduate level. The author uses a very simplified, accessible approach that de-emphasizes mathematical rigor. The presentation includes many diagrams to illustrate points being discussed and uses MATLAB for all of application code. The author reinforces concepts introduced in the book with easy to grasp review questions and problems, tailored to each specific chapter for better mastery of the subject matter. This book enables students to understand the fundamental concepts of wavelets and wavelet transforms, as well as how to use them for problem solutions in digital signal and image processing, mixed-signal testing, space applications, aerospace applications, biomedical, cyber security, homeland security and many other application areas.

Communications, Signal Processing, and Systems is a collection of contributions coming out of the International Conference on Communications, Signal Processing, and Systems (CSPS) held August 2012. This book provides the state-of-art developments of Communications, Signal Processing, and Systems, and their interactions in multidisciplinary fields, such as audio and acoustic signal processing. The book also examines Radar Systems, Chaos Systems, Visual Signal Processing and Communications and VLSI Systems and Applications. Written by experts and students in the fields of Communications, Signal Processing, and Systems.

This book presents the state-of-the-art and breakthrough innovations in design automation for cyber-physical systems.The authors discuss various aspects of cyber-physical systems design, including modeling, co-design, optimization, tools, formal methods, validation, verification, and case studies. Coverage includes a survey of the various existing cyber-physical systems functional design methodologies and related tools will provide the reader unique insights into the conceptual design of cyber-physical systems.

< p="" style=""> This highly informative and carefully presented book focuses on the fields of ergonomics/human factors and discusses the future of the community vis-a-vis health problems, productivity, aging, etc. Ergonomic intercession must be seen in light of its effect on productivity because ergonomic solutions will improve productivity as the reduction of environmental stressors, awkward postures and efforts lead to a reduction in task execution time. The book provides promising evidence that the field of ergonomics continues to thrive and develop deeper insights into how work environments, products and systems can be developed to meet needs, demands and limitations of humans and how they can support productivity improvements. Some of the themes covered are anthropometry and workplace design, biomechanics and modelling in ergonomics, cognitive and environmental ergonomics, ergonomic intervention and productivity, ergonomics in transport, mining, agriculture and forestry, health systems, work physiology and sports ergonomics, etc. This book is beneficial to academicians, policymakers and the industry alike. ^

Image processing and machine vision are fields of renewed interest in the commercial market. People in industry, managers, and technical engineers are looking for new technologies to move into the market. Many of the most promising developments are taking place in the field of image processing and its applications. The book offers a broad coverage of advances in a range of topics in image processing and machine vision.

The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and decomposition techniques such as Empirical Mode Decomposition, Independent Component Analysis and Singular Spectrum Analysis. The book is directed to the research students, professors, researchers and practitioners interested in exploring the advanced techniques in intelligent signal processing and data mining paradigms.

This book describes the signal, image and video processing methods and techniques for fire detection and provides a thorough and practical overview of this important subject, as a number of new methods are emerging. This book will serve as a reference for signal processing and computer vision, focusing on fire detection and methods for volume sensors. Applications covered in this book can easily be adapted to other domains, such as multi-modal object recognition in other safety and security problems, with scientific importance for fire detection, as well as video surveillance. Coverage includes: Camera Based Techniques Multi-modal/Multi-sensor fire analysis Pyro-electric Infrared Sensors for Flame Detection Large scale fire experiments Wildfire detection from moving aerial platforms

Capturing, recording and broadcasting the voice is often difficult. Many factors must be taken into account and achieving a true representation is much more complex than one might think. The capture devices such as the position of the singer(s) or narrator(s), the acoustics, atmosphere and equipment are just some of the physical aspects that need to be mastered. Then there is the passage through the analog or digital channel, which disrupts the audio signal, as well as the processes that are often required to enrich, improve or even transform the vocal timbre and tessitura. While in the past these processes were purely material, today digital technologies and software produce surprising results that every professional in recording and broadcasting should know how to master. Recording and Voice Processing 1 addresses some general theoretical concepts. A history of recording and the physiology of the vocal apparatus are detailed in order to give the reader an understanding of the fundamental aspects of the subject. This volume also includes an advanced study of microphones, addressing their characteristics and typologies. The acoustic environment and its treatment are also considered in terms of the location of the sound capture - whether in a home studio, recording studio, live or natural environment - in order to achieve a satisfactory sound recording.

The second volume will deal with a presentation of the main matrix and tensor decompositions and their properties of uniqueness, as well as very useful tensor networks for the analysis of massive data. Parametric estimation algorithms will be presented for the identification of the main tensor decompositions. After a brief historical review of the compressed sampling methods, an overview of the main methods of retrieving matrices and tensors with missing data will be performed under the low rank hypothesis. Illustrative examples will be provided.

This book describes the digitally intensive time-domain architectures and techniques applied to millimeter-wave frequency synthesis, with the objective of improving performance and reducing the cost of implementation. Coverage includes system architecture, system level modeling, critical building block design, and digital calibration techniques, making it highly suitable for those who want to learn about mm-wave frequency generation for communication and radar applications, integrated circuit implementation, and time-domain circuit and system techniques.

An up-to-date analysis of the SAR wavefront reconstruction signal theory and its digital implementation With the advent of fast computing and digital information processing techniques, synthetic aperture radar (SAR) technology has become both more powerful and more accurate. Synthetic Aperture Radar Signal Processing with MATLAB Algorithms addresses these recent developments, providing a complete, up-to-date analysis of SAR and its associated digital signal processing algorithms. This book introduces the wavefront reconstruction signal theory that underlies the best SAR imaging methods and provides clear guidelines to system design, implementation, and applications in diverse areas—from airborne reconnaissance to topographic imaging of ocean floors to surveillance and air traffic control to medical imaging techniques, and numerous others. Enabling professionals in radar signal and image processing to use synthetic aperture technology to its fullest potential, this work:

• Includes M-files to supplement this book that can be retrieved from The MathWorks anonymous FTP server at ftp://ftp.mathworks.com/pub/books/soumekh
• Provides practical examples and results from real SAR, ISAR, and CSAR databases
• Outlines unique properties of the SAR signal that cannot be found in other information processing systems
• Examines spotlight SAR, stripmap SAR, circular SAR, and monopulse SAR modalities
• Discusses classical SAR processing issues such as motion compensation and radar calibration

This fully updated and expanded textbook covers designing working systems at very high frequencies. The updated book includes new chapters on Circuit Board Layout Process and Circuit-Board Attacks and Security and more in-depth material on all the original chapters. As with the first edition, this book combines an intuitive, physics-based approach to electromagnetics with a focus on solving realistic problems. The book emphasizes an intuitive approach to electromagnetics, and then uses this foundation to show the reader how both physical phenomena can cause signals to propagate incorrectly; and how to solve commonly encountered issues. Emphasis is placed on real problems that the author has encountered in his professional career, integrating problem-solving strategies and real signal-integrity case studies throughout the presentation. Students are challenged to think about managing complex design projects and implementing successful engineering and manufacturing processes. For the new edition, the author designed a circuit board that illustrates many of the principles in the book, created instructor materials including PowerPoint slides, a homework bank, and a test bank, and created materials that departments can use for ABET assessment.

This book covers latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processing and their applications in real world. The topics covered in machine learning involves feature extraction, variants of support vector machine (SVM), extreme learning machine (ELM), artificial neural network (ANN) and other areas in machine learning. The mathematical analysis of computer vision and pattern recognition involves the use of geometric techniques, scene understanding and modelling from video, 3D object recognition, localization and tracking, medical image analysis and so on. Computational learning theory involves different kinds of learning like incremental, online, reinforcement, manifold, multi-task, semi-supervised, etc. Further, it covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. Additionally, it covers the recent developments to network intelligence for analyzing the network information and thereby adapting the algorithms dynamically to improve the efficiency. In the last, it includes the progress in signal processing to process the normal and abnormal categories of real-world signals, for instance signals generated from IoT devices, smart systems, speech, videos, etc., and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG) and electromyogram (EMG).

A practical, hands-on guide to embedded signal processing

This unique reference covers the basic concepts, principles, and theory behind digital signal processing (DSP), but emphasizes a learn-by-doing approach and focuses on real-time applications. Readers quickly learn to use the latest tools to design, simulate, and implement the algorithms for applications. Part A explores fundamental DSP concepts using software tools from MathWorks, Analog Devices, Inc. (ADI), and National Instruments (NI) Part B focuses on the design and implementation of embedded systems based on the Blackfin processor and introduces many design and development tools Part C focuses on designing and implementing real-time DSP applications The book includes experiments and exercises based on the Blackfin BF533 and BF537 EZ-KIT Lite boards; an accompanying FTP site provides additional exercises using the Blackfin simulator and other EZ-KIT Lite boards The companion Web site is updated continually to reflect the latest upgrades to Blackfin tools and processors Hands-on examples, quizzes, experiments, exercises, exercise problems, and application projects accelerate and enhance learning

This is an excellent desktop reference for practicing engineers and a combination workbook and textbook for undergraduate and graduate students in embedded signal processing design and/or real-time signal processing courses.