Signalbehandling

This book consists of selected peer-reviewed articles from the International Conference on Computer Vision, High Performance Computing, Smart Devices and Networks (CHSN-2020), held at JNTU, Kakinada, India. The theme and areas of the conference include vast scope for latest concepts and trends in communication engineering, information theory and networks, signal, image and speech processing, wireless and mobile communication, Internet of Things, and cybersecurity for societal causes and humanitarian applications.

AI to Prevent Remote Human-to-Human VR & Trafficking Program is a proposed program that would use artificial intelligence (AI) to prevent human trafficking in virtual reality (VR). The program would use a variety of AI techniques, including machine learning and deep learning, to detect suspicious activity in VR, identify victims and perpetrators of human trafficking, and educate and empower users about human trafficking and how to stay safe in VR.The program is still in the early stages of development, but it has the potential to be a powerful tool for preventing human trafficking in VR. VR is a new and emerging technology, and human traffickers have already begun to use it to exploit victims. AI can help to combat this by providing law enforcement and other organizations with the tools they need to identify and rescue victims of human trafficking in VR.The program is also designed to educate and empower users about human trafficking and how to stay safe in VR. This is important because many users are not aware of the risks associated with VR, and they may be more likely to be trafficked if they do not know how to protect themselves.The AI to Prevent Remote Human-to-Human VR & Trafficking Program is a promising new initiative that has the potential to make a real difference in the fight against human trafficking.

This contributed volume showcases the most significant results obtained from the DFG Priority Program on Compressed Sensing in Information Processing.  Topics considered revolve around timely aspects of compressed sensing with a special focus on applications, including compressed sensing-like approaches to deep learning; bilinear compressed sensing - efficiency, structure, and robustness; structured compressive sensing via neural network learning; compressed sensing for massive MIMO; and security of future communication and compressive sensing.

The book presents the proceedings of the 30th Biennial Symposium on Communications 2021 (BSC21), a prestigious international research conference in communications, information theory, and signal processing. Started in 1962 by Queen's University, Canada, the Symposium is now presented by the Canadian Society of Information Theory. Its 30th edition was hosted virtually by The University of Saskatchewan and held in Saskatoon from June 28 to 30, 2021. Topics include Communication and Information Theory, Coding and Signal Processing for Communications, and Multiple Antenna Systems and Cooperative Communications.

This book presents the design of modular architecture flight simulators. Safe transportation of people and goods is one of the main directions for the development of the world economy. At the same time, in conditions of constantly increasing intensity of air traffic, the actions of people, responsible for piloting aircraft and air traffic control are of particular importance. In this regard, special attention should be paid to the process of training such specialists. This book describes various flight simulators of an aircraft, as well as to assess the impact of various characteristics of aviation simulators on the quality of skills of aviation specialists. The book discusses the following issues:1) method of setting dynamic parameters;2) methods of correction of simulator parameters, according to expert opinions of operating organizations;3) modules of simulators of operation of various aircraft units and flight conditions;4) prospects for the development of aviation simulators;5) collection and evaluation of information in the process of training on aviation simulators.

This book offers an in-depth technical presentation of photography and details about the inner workings of the digital camera, while keeping the artistic principles in mind. Departing from the current stream, the book treats photography as a highly scientific and technical subject, and serves as a reference to those who seek for an understanding of the technical aspects relating to the photographic camera, the beating heart of photography. It offers insight on why the photographs are created the way they are, highlighting also the limitations. As the author of this book is an image technology scientist and a photography enthusiast who has been teaching photography for a long time, this treatise reflects his own constant search and study for an in-depth understanding.

This book features the proceedings of the 4th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (BDCC 2021). The papers feature detail on cognitive computing and its self-learning systems that use data mining, pattern recognition and natural language processing (NLP) to mirror the way the human brain works. This international conference focuses on technologies from knowledge representation techniques and natural language processing algorithms to dynamic learning approaches. Topics covered include Data Science for Cognitive Analysis, Real-Time Ubiquitous Data Science, Platform for Privacy Preserving Data Science, and Internet-Based Cognitive Platform.

"Signals & Systems" is a comprehensive textbook designed for undergraduate courses in electrical and electronics engineering. This essential guide covers fundamental concepts and techniques of signals and systems that are of critical importance in diverse engineering disciplines such as computer science, information technology, and more. The book lays out a parallel analysis for continuous and discrete-time signals and systems, providing insight into their similarities and differences. The presentation is clear, concise, and engaging with numerous examples to help readers better understand the theoretical concepts. It is the perfect book for students studying for their GATE/IES exams, as it covers all the topics according to their syllabus. The book is also packed with GATE previous papers' solved problems and chapter-wise objective questions at the end of each chapter. "Signals & Systems" is the go-to book for students who want to excel in the field of electrical and electronics engineering.

This book presents the proceedings of the 9th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2021), held at NIT Mizoram, Aizwal, Mizoram, India, during June 25 - 26, 2021. FICTA conference aims to bring together researchers, scientists, engineers, and practitioners to exchange their new ideas and experiences in the domain of intelligent computing theories with prospective applications to various engineering disciplines. This volume covers broad areas of Evolution in Computational Intelligence. The conference papers included herein presents both theoretical as well as practical aspects of different areas like ANN and genetic algorithms, human-computer interaction, intelligent control optimization, evolutionary computing, intelligent e-learning systems, machine learning, mobile computing, multi-agent systems, etc. The volume will also serve as a knowledge centre for students of post-graduate level in various engineering disciplines.

This book describes the use of advance signal processing techniques for different Industry 4.0 applications, including: Non-destructive testing, Decisions under Parametric Uncertainty, Deep learning for industrial sector, Energy-efficient Industry 4.0 etc. The book will help readers to understand future needs of industries.

This book investigates the image watermarking domain, analyzing and comparing image watermarking techniques that exist in current literature. The author¿s goal is to aid researchers and students in their studies in the vast and important domain of image watermarking, including its advantages and risks. The book has three chapters: image watermarking using data compression; speech modulation for image watermarking; and secure image watermarking based on LWT and SVD.In addition, this book: Investigates the image watermarking domain, analyzing and comparing current image watermarking techniquesIncludes detail on image encryption and mathematical tools used for image watermarkingCovers image watermarking using data compression, speech modulation for image watermarking, and more

This book discusses the Versatile Video Coding (VVC), the ISO and ITU state-of-the-art video coding standard. VVC reaches a compression efficiency significantly higher than its predecessor standard (HEVC) and it has a high versatility for efficient use in a broad range of applications and different types of video content, including Ultra-High Definition (UHD), High-Dynamic Range (HDR), screen content, 360 videos, and resolution adaptivity. The authors introduce the novel VVC tools for block partitioning, intra-frame and inter-frames predictions, transforms, quantization, entropy coding, and in-loop filtering. The authors also present some solutions exploring VVC encoding behavior at different levels to accelerate the intra-frame prediction, applying statistical-based heuristics and machine learning (ML) techniques.

This book is designed to serve as a textbook for courses offered to undergraduate students enrolled in the Electrical, Electronics, Communications, and Instrumentation Engineering disciplines. The book presents a clear and comprehensive introduction to digital signal processing. For easier comprehension, the course contents of all the chapters are in sequential order. A variety of examples and solved problems are included in the book to enable application and ease of understanding of theoretical concepts. Every chapter contains several homework problems with answers followed by question-and-answer-type assignments. The detailed coverage and pedagogical tools make this an ideal textbook for students and researchers enrolled in electrical engineering and related programs.

Signal processing traditionally relies on classical statistical modeling techniques. Such model-based methods utilize mathematical formulations that represent the underlying physics, prior information and additional domain knowledge. Simple classical models are useful but sensitive to inaccuracies and may lead to poor performance when real systems display complex or dynamic behavior. More recently, deep learning approaches that use highly parametric deep neural networks (DNNs) are becoming increasingly popular. Deep learning systems do not rely on mathematical modeling, and learn their mapping from data, which allows them to operate in complex environments. However, they lack the interpretability and reliability of model-based methods, typically require large training sets to obtain good performance, and tend to be computationally complex. Model-based signal processing methods and data-centric deep learning each have their pros and cons. These paradigms can be characterized as edges of a continuous spectrum varying in specificity and parameterization. The methodologies that lie in the middle ground of this spectrum, thus integrating model-based signal processing with deep learning, are referred to as model-based deep learning, and are the focus here. This monograph provides a tutorial style presentation of model-based deep learning methodologies. These are families of algorithms that combine principled mathematical models with data-driven systems to benefit from the advantages of both approaches. Such model-based deep learning methods exploit both partial domain knowledge, via mathematical structures designed for specific problems, as well as learning from limited data. The monograph includes running signal processing examples, in super-resolution, tracking of dynamic systems, and array processing. It is shown how they are expressed using the provided characterization and specialized in each of the detailed methodologies. The aim is to facilitate the design and study of future systems at the intersection of signal processing and machine learning that incorporate the advantages of both domains. The source code of the numerical examples are available and reproducible as Python notebooks.

This book focuses on current and innovative technologies in perinatal medicine, specifically the period from the third trimester of pregnancy up to one month after birth. It follows the Second International Summer School on Technologies and Signal Processing in Perinatal Medicine (TSPPM 2021) and includes a number of the master lectures presented at the school. The book aims to provide an overview of current data processing and machine learning approaches, with clear indications and exhaustive presentations on research trends in the field, written by top scientists and researchers. It also presents the underlying clinical aspects and ethico-legal issues associated with the adoption of these technologies, particularly artificial intelligence tools. Innovative Technologies and Signal Processing in Perinatal Medicine: Volume 2 provides students, researchers, and practitioners with the knowledge necessary to carry out basic and applied research on the development of perinatal medicine medical devices with a particular emphasis on software design and development.

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). 

The official publication of the Railway Signal Association, this journal provides in-depth coverage of issues and developments in railway signaling technology, including articles on equipment, components, maintenance, testing, and more. Aimed at professionals in the field, this journal also offers valuable insights for anyone interested in the latest advances in railway safety and communications.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it.This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

This book provides a comprehensive guide to 3D Light-Field camera based imaging, exploring the working principles, developments and its applications in fluid mechanics and aerodynamics measurements. It begins by discussing the fundamentals of Light-Field imaging and theoretical resolution analysis, before touching upon the detailed optics design and micro-lens array assembly. Subsequently, Light-Field calibration methods that compensate for optical distortions and establish the relations between the image and real-word 3D coordinates are covered. This is followed by Light-Field 3D reconstruction algorithms which are elaborated for micrometer-scale particles and centimeter-scale physical models. Last but not least, implementations of the preceding procedures to selected fundamental and applied flow measurement scenarios are provided at the end of the book.  Development and Application of Light-Field Cameras in Fluid Measurements gives an in-depth analysis of each topic discussed, making it ideal as both an introductory and reference guide for researchers and postgraduates interested in 3D flow measurements.

This book explains the motivation for using microphone arrays as opposed to using a single sensor for sound acquisition. The book then goes on to summarize the most useful ideas, concepts, results, and new algorithms therein. The material presented in this work includes analysis of the advantages of using microphone arrays, including dimensionality reduction to remove the redundancy while preserving the variability of the array signals using the principal component analysis (PCA). The authors also discuss benefits such as beamforming with low-rank approximations, fixed, adaptive, and robust distortionless beamforming, differential beamforming, and a new form of binaural beamforming that takes advantage of both beamforming and human binaural hearing properties to improve speech intelligibility. The book makes the microphone array signal processing theory and applications available in a complete and self-contained text. The authors attempt to explain the main ideas in a clear and rigorous way so that the reader can easily capture the potentials, opportunities, challenges, and limitations of microphone array signal processing. This book is written for those who work on the topics of microphone arrays, noise reduction, speech enhancement, speech communication, and human-machine speech interfaces.

Im vorliegenden Buch wird eine neue EMV-Filtermaßnahme eingeführt, die auf dem piezoelektrischen Effekt basiert. Piezoelektrische EMV-Filter (PEF) erzeugen bei ihren Resonanzfrequenzen einen niederimpedanten Ausbreitungspfad für leitungsgebundene elektromagnetische Störungen. Dies ermöglicht eine Unterdrückung diskreter Störspitzen. Jenseits der Resonanzen verhalten sich PEF kapazitiv. PEF können daher nicht nur reguläre Funkentstörkondensatoren, wie z.B. Y-Kondensatoren, ersetzen, sondern ermöglichen zusätzlich eine selektive Dämpfung bei dezidierten Störfrequenzen. Es wird gezeigt, dass sich durch Verwendung eines PEF ein kompakterer EMV-Filter realisieren lässt. Hiermit werden Abmessungen, Gewicht und letztendlich die Kosten von EMV-Maßnahmen wesentlich reduziert.

Quantitative ultrasound (QUS) continues to mature as a research field and is primed to make a swift transition to routine preclinical and clinical applications. This book will serve two main purposes:Advanced education in QUS by providing a complete and thorough review of all theoretical, physical, and engineering aspects of QUS.Review of recent development of QUS by lead contributors in the research field.This 2nd edition will focus on 6 modern research topics related to quantitative ultrasound of soft tissues:Spectral-based methods for tissue characterization, tissue typing, cancer detection, etc.Attenuation estimation for tissue characterization and improving spectral based methodsEnvelope statistics analysis as a means of quantifying and imaging tissue properties.Ultrasound computed tomography for preclinical and clinical imaging.Scanning acoustic microscopy for formingimages of mechanical properties of soft tissues with micron resolution.Phantoms for quantitative ultrasound.

This book teaches the fundamentals and mathematical formulas of reversible transformations (or transforms) that are used in many source coding and signal processing systems. These mathematical transforms are often necessary or crucial toward reduction of data storage and transmission rate requirements. The author emphasizes the wavelet transform as it is the preferred transform for practical application in many coding and signal processing systems. The book also covers the tap (coefficient) values for some of those filters that satisfy the perfect reconstruction property. Examples of the use of filter-based and matrix-based transforms are also provided. This self-contained work contains insight gained through research and practice, which makes it a valuable reference and tutorial for readers interested in the subject of mathematical transforms.This book:Teaches the fundamentals and mathematical formulas of reversible transformations, as well as theirapplicationsHighlights the wavelet transformation, which is the preferred transform for many practical applicationsContains insight gained through research and practice, making it a valuable resource those interested in the topic

The book focuses on utilizing sparse signal processing techniques in designing massive MIMO communication systems. As the number of antennas has been increasing rapidly for years, extremely high-dimensional channel matrix and massive user access urge for algorithms with much higher efficiency. This book provides in-depth discussions on compressive sensing techniques and simulates the performance on wireless systems. The easy-to-understand instructions with detailed simulations and open-sourced codes provide convenience for readers such as researchers, engineers, and graduate students in the fields of wireless communications.

This book provides an interdisciplinary look at emerging trends in signal processing and biomedicine found at the intersection of healthcare, engineering, and computer science. Bringing together expanded versions of selected papers presented at the 2020 IEEE Signal Processing in Medicine and Biology Symposium (IEEE SPMB), it examines the vital role signal processing plays in enabling a new generation of technology based on big data and looks at applications ranging from medical electronics to data mining of electronic medical records. Topics covered include analysis of medical images, machine learning, biomedical nanosensors, wireless technologies, and instrumentation and electrical stimulation. Biomedical Sensing and Analysis: Signal Processing in Medicine and Biology presents tutorials and examples of successful applications, and will appeal to a wide range of professionals, researchers, and students interested in applications of signal processing, medicine, and biology.Presents an interdisciplinary look at research trends in signal processing and biomedicine;Promotes collaboration between healthcare practitioners and signal processing researchers;Includes tutorials and examples of successful applications.