New technology in vehicles is transforming the way people move around as well as what they do in their vehicles. How does one communicate with an in-car speech system and how does this vary by language or cultural community? This book explores this process by focusing on the communication practices that people engage in when using their in-car systems and when talking about their vehicles with co-passengers. Chapters present a robust theory and methodology for studying communication in cars, how tasks are begun and ended, how people switch between tasks, how non-task talk appears, what ways and styles of communication drivers prefer, and how they expect the system voice to respond, among other things. Particular attention is given to cultural preferences as they are evident in this communication; these preferences are found to ground various trajectories in the use and meaning of in-car communication practices. The book explores these matters with a focus on the United States and Mainland China. Implications are drawn for the design and utilization of in-car communication systems.

The book presents selected, extended and peer reviewed papers from the International Multiconference on System, Automation and Control held Leipzig in 2018. These are complemented with solicited contributions by international experts. Main topics are automatic control, robotics, synthesis of automation systems. Application examples range from man-machine interaction, mechatronics, on to biological and economical models.

The book covers the most recent developments in machine learning, signal analysis, and their applications. It covers the topics of machine intelligence such as: deep learning, soft computing approaches, support vector machines (SVMs), least square SVMs (LSSVMs) and their variants; and covers the topics of signal analysis such as: biomedical signals including electroencephalogram (EEG), magnetoencephalography (MEG), electrocardiogram (ECG) and electromyogram (EMG) as well as other signals such as speech signals, communication signals, vibration signals, image, and video. Further, it analyzes normal and abnormal categories of real-world signals, for example normal and epileptic EEG signals using numerous classification techniques. The book is envisioned for researchers and graduate students in Computer Science and Engineering, Electrical Engineering, Applied Mathematics, and Biomedical Signal Processing.

Get to grips with the principles and practice of signal processing used in mobile communications systems. Focusing particularly on speech, video, and modem signal processing, pioneering experts employ a detailed, top-down analytical approach to outline the network architectures and protocol structures of multiple generations of mobile communications systems, identify the logical ranges where media and radio signal processing occur, and analyze the procedures for capturing, compressing, transmitting, and presenting media. Chapters are uniquely structured to show the evolution of network architectures and technical elements between generations up to and including 5G, with an emphasis on maximizing service quality and network capacity through re-using existing infrastructure and technologies. Implementation examples and data taken from commercial networks provide an in-depth insight into the operation of real mobile communications systems, including GSM, cdma2000, W-CDMA, LTE, and LTE-A, making this a practical, hands-on guide for both practicing engineers and graduate students in wireless communications.

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.

Signals and Systems: Analysis Using Transform Methods and MATLAB (R) has been extensively updated, while retaining the emphasis on fundamental applications and theory. The text includes a wealth of exercises, including drill exercises, and more challenging conceptual problems. McGraw-Hill's Connect, is also available as an optional, add on item. Connect is the only integrated learning system that empowers students by continuously adapting to deliver precisely what they need, when they need it, how they need it, so that class time is more effective. Connect allows the professor to assign homework, quizzes, and tests easily and automatically grades and records the scores of the student's work. Problems are randomized to prevent sharing of answers an may also have a "multi-step solution" which helps move the students' learning along if they experience difficulty.

The Poisson process, a core object in modern probability, enjoys a richer theory than is sometimes appreciated. This volume develops the theory in the setting of a general abstract measure space, establishing basic results and properties as well as certain advanced topics in the stochastic analysis of the Poisson process. Also discussed are applications and related topics in stochastic geometry, including stationary point processes, the Boolean model, the Gilbert graph, stable allocations, and hyperplane processes. Comprehensive, rigorous, and self-contained, this text is ideal for graduate courses or for self-study, with a substantial number of exercises for each chapter. Mathematical prerequisites, mainly a sound knowledge of measure-theoretic probability, are kept in the background, but are reviewed comprehensively in the appendix. The authors are well-known researchers in probability theory; especially stochastic geometry. Their approach is informed both by their research and by their extensive experience in teaching at undergraduate and graduate levels.

For advanced students of network data science, this compact account covers both well-established methodology and the theory of models recently introduced in the graphical model literature. It focuses on the discrete case where all variables involved are categorical and, in this context, it achieves a unified presentation of classical and recent results.

This snapshot of the current frontier of statistics and network analysis focuses on the foundational topics of modeling, sampling, and design. Primarily for graduate students and researchers in statistics and closely related fields, emphasis is not only on what has been done, but on what remains to be done.

A comprehensive collection of fundamental principles and applications of analog electronic circuits, including semiconductor diodes, bipolar junction transistors, field-effect transistors (FETs), operational amplifiers, power amplifiers, and feedback circuits. With abundant practical examples, it is an essential reference for researchers, students and engineers in electronical engineering and information processing.

Social Signal Processing is the first book to cover all aspects of the modeling, automated detection, analysis, and synthesis of nonverbal behavior in human-human and human-machine interactions. Authoritative surveys address conceptual foundations, machine analysis and synthesis of social signal processing, and applications. Foundational topics include affect perception and interpersonal coordination in communication; later chapters cover technologies for automatic detection and understanding such as computational paralinguistics and facial expression analysis and for the generation of artificial social signals such as social robots and artificial agents. The final section covers a broad spectrum of applications based on social signal processing in healthcare, deception detection, and digital cities, including detection of developmental diseases and analysis of small groups. Each chapter offers a basic introduction to its topic, accessible to students and other newcomers, and then outlines challenges and future perspectives for the benefit of experienced researchers and practitioners in the field.

Gain a detailed understanding of the protocols, network architectures and techniques being considered for 5G wireless networks with this authoritative guide to the state of the art. * Get up to speed with key topics such as cloud radio access networks, mobile edge computing, full duplexing, massive MIMO, mmWave, NOMA, Internet of things, M2M communications, D2D communications, mobile data offloading, interference mitigation techniques, radio resource management, visible light communications, and smart data pricing. * Learn from leading researchers in academia and industry about the most recent theoretical developments in the field. * Discover how each potential technology can increase the capacity, spectral efficiency, and energy efficiency of wireless systems. Providing the most comprehensive overview of 5G technologies to date, this is an essential reference for researchers, practicing engineers and graduate students working in wireless communications and networking.

Written by pioneers of the concept, this is the first complete guide to the physical and engineering principles of Massive MIMO. Assuming only a basic background in communications and statistical signal processing, it will guide readers through key topics in multi-cell systems such as propagation modeling, multiplexing and de-multiplexing, channel estimation, power control, and performance evaluation. The authors' unique capacity-bounding approach will enable readers to carry out effective system performance analyses and develop advanced Massive MIMO techniques and algorithms. Numerous case studies, as well as problem sets and solutions accompanying the book online, will help readers put knowledge into practice and acquire the skill set needed to design and analyze complex wireless communication systems. Whether you are a graduate student, researcher, or industry professional working in the field of wireless communications, this will be an indispensable guide for years to come.

This thoroughly updated new edition presents state-of-the-art sparse and multiscale image and signal processing. It covers linear multiscale geometric transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Along with an up-to-the-minute description of required computation, it covers the latest results in inverse problem solving and regularization, sparse signal decomposition, blind source separation, in-painting, and compressed sensing. New chapters and sections cover multiscale geometric transforms for three-dimensional data (data cubes), data on the sphere (geo-located data), dictionary learning, and nonnegative matrix factorization. The authors wed theory and practice in examining applications in areas such as astronomy, including recent results from the European Space Agency's Herschel mission, biology, fusion physics, cold dark matter simulation, medical MRI, digital media, and forensics. MATLAB (R) and IDL code, available online at www.SparseSignalRecipes.info, accompany these methods and all applications.

This graduate textbook explains image reconstruction technologies based on region-based binocular and trinocular stereo vision, and object, pattern and relation matching. It further discusses principles and applications of multi-sensor fusion and content-based retrieval. Rich in examples and excises, the book concludes image engineering studies for electrical engineering and computer science students.

This graduate textbook explains image geometry, and elaborates on image enhancement in spatial and frequency domain, unconstrained and constrained restoration and restoration from projection, and discusses various coding technologies such as predictive coding and transform coding. Rich in examples and exercises, it prepares electrical engineering and computer science students for further studies on image analysis and understanding.

Balancing theoretical analysis and practical advice, this book describes all the underlying principles required to build high performance indoor optical wireless communication (OWC) systems based on visible and infrared light, alongside essential techniques for optimising systems by maximising throughput, reducing hardware complexity and measuring performance effectively. It provides a comprehensive analysis of information rate-, spectral- and power-efficiencies for single and multi-carrier transmission schemes, and a novel analysis of non-linear signal distortion, enabling the use of off-the-shelf LED technology. Other topics covered include cellular network throughput and coverage, static resource partitioning and dynamic interference-aware scheduling, realistic light propagation modelling, OFDM, optical MIMO transmission and nonlinearity modelling. Covering practical techniques for building indoor optical wireless cellular networks supporting multiple users and guidelines for 5G cellular system studies, in addition to physical layer issues, this is an indispensable resource for academic researchers, professional engineers and graduate students working in optical communications.

Amazon.com's Top-Selling DSP Book for Seven Straight Years--Now Fully Updated " ""Understanding Digital Signal Processing, Third Edition, "is quite simply the best resource for engineers and other technical professionals who want to master and apply today's latest DSP techniques. Richard G. Lyons has updated and expanded his best-selling second edition to reflect the newest technologies, building on the exceptionally readable coverage that made it the favorite of DSP professionals worldwide. He has also added hands-on problems to every chapter, giving students even more of the practical experience they need to succeed. Comprehensive in scope and clear in approach, this book achieves the perfect balance between theory and practice, keeps math at a tolerable level, and makes DSP exceptionally accessible to beginners without ever oversimplifying it. Readers can thoroughly grasp the basics and quickly move on to more sophisticated techniques. This edition adds extensive new coverage of FIR and IIR filter analysis techniques, digital differentiators, integrators, and matched filters. Lyons has significantly updated and expanded his discussions of multirate processing techniques, which are crucial to modern wireless and satellite communications. He also presents nearly twice as many DSP Tricks as in the second edition--including techniques even seasoned DSP professionals may have overlooked. Coverage includesNew homework problems that deepen your understanding and help you apply what you've learnedPractical, day-to-day DSP implementations and problem-solving throughoutUseful new guidance on generalized digital networks, including discrete differentiators, integrators, and matched filtersClear descriptions of statistical measures of signals, variance reduction by averaging, and real-world signal-to-noise ratio (SNR) computationA significantly expanded chapter on sample rate conversion (multirate systems) and associated filtering techniquesNew guidance on implementing fast convolution, IIR filter scaling, and moreEnhanced coverage of analyzing digital filter behavior and performance for diverse communications and biomedical applicationsDiscrete sequences/systems, periodic sampling, DFT, FFT, finite/infinite impulse response filters, quadrature (I/Q) processing, discrete Hilbert transforms, binary number formats, and much more

The brief focuses on applying sublinear algorithms to manage critical big data challenges. The text offers an essential introduction to sublinear algorithms, explaining why they are vital to large scale data systems. It also demonstrates how to apply sublinear algorithms to three familiar big data applications: wireless sensor networks, big data processing in Map Reduce and smart grids. These applications present common experiences, bridging the theoretical advances of sublinear algorithms and the application domain. Sublinear Algorithms for Big Data Applications is suitable for researchers, engineers and graduate students in the computer science, communications and signal processing communities.

"Think DSP: Digital Signal Processing in Python" is an introduction to signal processing and system analysis using a computational approach. The premise of this book (like the others in the Think X series) is that if you know how to program, you can use that skill to learn other things. By the end of the first chapter, you'll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds. Subsequent chapters follow a logical progression that develops the important ideas incrementally, with a focus on applications.

This proceedings set contains 85 selected full papers presented at the 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences - MCO 2015, held on May 11-13, 2015 at Lorraine University, France. The present part I of the 2 volume set includes articles devoted to Combinatorial optimization and applications, DC programming and DCA: thirty years of Developments, Dynamic Optimization, Modelling and Optimization in financial engineering, Multiobjective programming, Numerical Optimization, Spline Approximation and Optimization, as well as Variational Principles and Applications.

The subject of Digital Signal Processing (DSP) is enormously complex, involving many concepts, probabilities, and signal processing that are woven together in an intricate manner. To cope with this scope and complexity, many DSP texts are often organized around the "numerical examples" of a communication system. With such organization, readers can see through the complexity of DSP, they learn about the distinct concepts and protocols in one part of the communication system while seeing the big picture of how all parts fit together. From a pedagogical perspective, our personal experience has been that such approach indeed works well.Based on the authors' extensive experience in teaching and research, Digital Signal Processing: a breadth-first approach is written with the reader in mind. The book is intended for a course on digital signal processing, for seniors and undergraduate students. The subject has high popularity in the field of electrical and computer engineering, and the authors consider all the needs and tools used in analysis and design of discrete time systems for signal processing.Key features of the book include:* The extensive use of MATLAB based examples to illustrate how to solve signal processing problems. The textbook includes a wealth of problems, with solutions* Worked-out examples have been included to explain new and difficult concepts, which help to expose the reader to real-life signal processing problems* The inclusion of FIR and IIR filter design further enrich the contents

Compressed Sensing (CS) is a promising method that recovers the sparse and compressible signals from severely under-sampled measurements. CS can be applied to wireless communication to enhance its capabilities. As this technology is proliferating, it is possible to explore its need and benefits for emerging applicationsCompressive Sensing for Wireless Communication provides:* A clear insight into the basics of compressed sensing* A thorough exploration of applying CS to audio, image and computer vision* Different dimensions of applying CS in Cognitive radio networks* CS in wireless sensor network for spatial compression and projection* Real world problems/projects that can be implemented and tested* Efficient methods to sample and reconstruct the images in resource constrained WMSN environmentThis book provides the details of CS and its associated applications in a thorough manner. It lays a direction for students and new engineers and prepares them for developing new tasks within the field of CS. It is an indispensable companion for practicing engineers who wish to learn about the emerging areas of interest.

The book explains in a comprehensive way the basic terms of communication engineering, giving a proper amount of the needed mathematical background and explanations of the physical nature of the problems. The theory of communication sciences is explained by using knowledge and examples from real-world applications. The information is presented in a way that is understandable also for those who are not directly involved in communication sciences, but would like to learn more about them.