Clock synchronization is a mechanism for providing a standard reference time to various devices across a distributed network. It is critical in modern computer networks because every aspect of managing, securing, planning, and debugging a network involves determining when particular events happen. Global Positioning Systems (GPS) are a popular mechanism for achieving synchronization, but these are not always practical in network systems. This monograph concentrates on a technique called Network Time Distribution which is often more cost-effective than GPS-based timing, as it does not require any dedicated hardware and can often make use of the existing network resources for synchronizing devices across the network. The technique uses a master/slave construction to synchronize the time throughout devices on a network. To do this, two-way message exchange is required which can be subject to network delays. The authors present recent developments to combat the degrading effects of stochastic delays for clock synchronization protocols based on two-way message exchange. While the techniques presented in the monograph apply to many applications and any clock synchronization protocol based on two-way message exchanges, the authors mainly discuss the applications in the context of IEEE 1588 PTP standard applied to telecommunication networks. Recent Advances in Clock Synchronization for Packet-Switched Networks is of interest to telecommunication engineers designing and building a broad range of telecommunication systems. It provides an introduction to the theory as well as practical results for implementation in real-world systems.

Combining clear explanations of elementary principles, advanced topics and applications with step-by-step mathematical derivations, this textbook provides a comprehensive yet accessible introduction to digital signal processing. All the key topics are covered, including discrete-time Fourier transform, z-transform, discrete Fourier transform and FFT, A/D conversion, and FIR and IIR filtering algorithms, as well as more advanced topics such as multirate systems, the discrete cosine transform and spectral signal processing. Over 600 full-color illustrations, 200 fully worked examples, hundreds of end-of-chapter homework problems and detailed computational examples of DSP algorithms implemented in MATLAB (R) and C aid understanding, and help put knowledge into practice. A wealth of supplementary material accompanies the book online, including interactive programs for instructors, a full set of solutions and MATLAB (R) laboratory exercises, making this the ideal text for senior undergraduate and graduate courses on digital signal processing.

The book addresses the current demand for a scientific approach to advanced wireless technology and its future developments, including the current move from 4G to 5G wireless systems (2020), and the future to 6G wireless systems (2030). It gives a clear and in-depth presentation of both antennas and the adaptive signal processing that makes antennas powerful, maneuverable, and necessary for advanced wireless technology. Moving towards the increasing demand for a scientific approach to smart antennas, the book presents electromagnetic signal processing techniques to both control the antenna beam and to track the moving station, which is required for effective, fast, dynamic beamforming. In addition to presenting new, memory efficient and fast algorithms for smart antennas, another helpful feature of the book is the inclusion of complete listings of MATLABTM codes for powerful techniques such as Artificial Intelligence (AI) beamforming, Analytical Phase Shift technique and the traditional Least Mean Square method, The student, researcher or engineer may readily use these codes to gain confidence in understanding, as well as to develop and deploy powerful, new smart antenna techniques. The first part of the book presents a comprehensive description and analysis of basic antenna theory, starting from short dipole antennas to array antennas. This section also includes important concepts related to antenna parameters, electromagnetic wave propagation, the Friis equation, the radar equation and wave reflection and transmission through media. The second part of the book focuses on smart antennas, commencing from a look at traditional approach to beam forming before getting into the details of smart antennas. Complete derivation and description of the techniques for electromagnetic field signal processing techniques for adaptive beam forming are presented. Many new and research ideas are included in this section. A novel method for fast, low memory and accurate, maneuverable single beam generation is presented, as well as other methods for beamforming with fewer elements with a simple method for tracking the mobile antenna and station. In this section, for completeness, the use of antenna signal processing for synthetic aperture techniques for imaging are also presented, specifically the Inverse Synthetic Aperture Imaging technique. Some computer codes are given for the student and researcher to get started with new areas to explore. The third part of the book presents technological aspects of advanced wireless technology, including Artificial Intelligence driven steerable single beams, the 5G wireless system and the various devices needed to construct the system. While the books' main emphasis is theoretical understanding and design with the basic tools needed to develop powerful computer code for the smart antennas, it also provides the algorithms or codes in a number of important cases to show how the smart antenna computer codes may be developed using electromagnetic signal processing. Artificial Intelligence (AI) driven beam forming is presented using computationally fast and low-memory demanding technique for AI beam forming is presented with the different excitation functions available. The final chapter outlines certain techniques to develop smart antenna algorithms and computer codes for beginners, researchers, and engineers, and furthermore, to implement a part of what was learnt, including AI techniques.

Advances in Imaging and Electron Physics, Volume 216, merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy and the computing methods used in all these domains.

Advances in Imaging and Electron Physics, Volume 215, merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy and the computing methods used in all these domains.

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.

Many natural signals possess only a few degrees of freedom. For instance, the occupied radio spectrum may be intermittently concentrated to only a few frequency bands of the system bandwidth. This special structural feature - signal sparsity - is conducive in designing efficient signal processing techniques for wireless networks. In particular, the signal sparsity can be leveraged by the recently emerged joint sampling and compression paradigm, compressed sensing (CS). This monograph reviews several recent CS advancements in wireless networks with an aim to improve the quality of signal reconstruction or detection while reducing the use of energy, radio, and computation resources. The monograph covers a diversity of compressive data reconstruction, gathering, and detection frameworks in cellular, cognitive, and wireless sensor networking systems. The monograph first gives an overview of the principles of CS for the readers unfamiliar with the topic. For the researchers knowledgeable in CS, the monograph provides in-depth reviews of several interesting CS advancements in designing tailored CS reconstruction techniques for wireless applications. The monograph can serve as a basis for the researchers intended to start working in the field, and altogether, lays a foundation for further research in the covered areas.

Biomedical imaging is a vast and diverse field. There are a plethora of imaging devices using light, X-rays, sound waves, magnetic fields, electrons, or protons, to measure structures ranging from nano to macroscale. In many cases, computer software is needed to turn the signals collected by the hardware into a meaningful image. These computer algorithms are similarly diverse and numerous.This survey presents a wide swath of biomedical image reconstruction algorithms under a single framework. It is a coherent, yet brief survey of some six decades of research. The underpinning theory of the techniques are described and practical considerations for designing reconstruction algorithms for use in biomedical systems form the central theme of each chapter. The unifying framework deployed throughout the monograph models imaging modalities as combinations of a small set of building blocks, which identify connections between modalities. Thus, the user can quickly port ideas and computer code from one to the next. Furthermore, reconstruction algorithms can treat the imaging model as a black. box, meaning that one algorithm can work for many modalities. This provides a pragmatic approach to designing effective reconstruction algorithms.This monograph is written in a tutorial style that concisely introduces students, researchers and practitioners to the development and design of effective biomedical image reconstruction algorithms.

Seismic data must be interpreted using digital signal processing techniques in order to create accurate representations of petroleum reservoirs and the interior structure of the Earth. This book provides an advanced overview of digital signal processing (DSP) and its applications to exploration seismology using real-world examples. The book begins by introducing seismic theory, describing how to identify seismic events in terms of signals and noise, and how to convert seismic data into the language of DSP. Deterministic DSP is then covered, together with non-conventional sampling techniques. The final part covers statistical seismic signal processing via Wiener optimum filtering, deconvolution, linear-prediction filtering and seismic wavelet processing. With over sixty end-of-chapter exercises, seismic data sets and data processing MATLAB codes included, this is an ideal resource for electrical engineering students unfamiliar with seismic data, and for Earth Scientists and petroleum professionals interested in DSP techniques.

In der hochbitratigen optischen Nachrichtentechnik ist es wichtig, parasitare induktive und kapazitive Einflusse auf die Funktion von Laser- und Fotodioden zu kompensieren. Wegen des nichtlinearen Charakters der u-i-Relationen der Induktivitaten, Kapazitaten und Widerstande ist es moeglich, Kompensationsverfahren gegen parasitare Effekte zu entwickeln oder die Nichtlinearitaten gezielt zur Signalubertragung einzusetzen. Reiner Thiele beweist, dass bei Applikation der vorgestellten Kompensationsverfahren kapazitive und induktive Influenzen auf die Grundfunktion der optoelektronischen Bauelemente vermeidbar sind, das Klemmenverhalten durch die u-i-Kennlinien von Laser- oder Fotodioden komplett erfasst wird und ungunstige Einflusse der Systemumgebung auf die optoelektronischen Schaltungen vermieden werden. Ausserdem stellt er Definitionen fur optoelektronische Grundstromkreise sowie ihre Berechnung fur die Applikation gleichartiger Laser- oder Fotodioden als Sende- bzw. Empfangsbauelemente der optischen Nachrichtentechnik vor. Der Autor: Prof. Dr.-Ing. Reiner Thiele lehrte an der Hochschule Zittau/Goerlitz und unterrichtet derzeit an der Staatlichen Studienakademie Bautzen.

Dielectric Metamaterials: Fundamentals, Designs, and Applications links fundamental Mie scattering theory with the latest dielectric metamaterial research, providing a valuable reference for new and experienced researchers in the field. The book begins with a historical, evolving overview of Mie scattering theory. Next, the authors describe how to apply Mie theory to analytically solve the scattering of electromagnetic waves by subwavelength particles. Later chapters focus on Mie resonator-based metamaterials, starting with microwaves where particles are much smaller than the free space wavelengths. In addition, several chapters focus on wave-front engineering using dielectric metasurfaces and the nonlinear optical effects, spontaneous emission manipulation, active devices, and 3D effective media using dielectric metamaterials.

Many processes in nature arise from the interaction of periodic phenomena with random phenomena. The results are processes that are not periodic, but whose statistical functions are periodic functions of time. These processes are called cyclostationary and are an appropriate mathematical model for signals encountered in many fields including communications, radar, sonar, telemetry, acoustics, mechanics, econometrics, astronomy, and biology. Cyclostationary Processes and Time Series: Theory, Applications, and Generalizations addresses these issues and includes the following key features.

Advances in Imaging and Electron Physics, Volume 212, merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy and the computing methods used in all these domains.

Electromagnetic imaging has been a powerful technique in various civil and military applications across medical imaging, geophysics, and space exploration. The Nyquist-Shannon theory has formed the basis for processing the signals in such systems. The advent of Compressive Sensing techniques has enabled low-dimension-model-based techniques to be used to break many of the bottlenecks of the earlier technologies. Low-dimensional-model-based electromagnetic imaging remains at its early stage, and many important issues relevant to practical applications need to be carefully investigated. In particular, this is the era of big data with booming electromagnetic sensing, by which massive data are being collected for retrieving very detailed information of probed objects. This monograph gives an overview of the low-dimensional models of structure signals, along with its relevant theories and low-complexity algorithms of signal recovery. It further reviews the recent advancements of low-dimensional-model-based electromagnetic imaging in various applied areas. It is a comprehensive introduction for researchers and engineers wishing to understand the state-of-the-art of electromagnetic imaging.

Advances in Imaging and Electron Physics, Volume 211, merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy and the computing methods used in all these domains.