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This book takes a comprehensive study on turbo message passing algorithms for structured signal recovery, where the considered structured signals include 1) a sparse vector/matrix (which corresponds to the compressed sensing (CS) problem), 2) a low-rank matrix (which corresponds to the affine rank minimization (ARM) problem), 3) a mixture of a sparse matrix and a low-rank matrix (which corresponds to the robust principal component analysis (RPCA) problem). The book is divided into three parts. First, the authors introduce a turbo message passing algorithm termed denoising-based Turbo-CS (D-Turbo-CS). Second, the authors introduce a turbo message passing (TMP) algorithm for solving the ARM problem. Third, the authors introduce a TMP algorithm for solving the RPCA problem which aims to recover a low-rank matrix and a sparse matrix from their compressed mixture. With this book, we wish to spur new researches on applying message passing to various inference problems. Provides an in depth look into turbo message passing algorithms for structured signal recovery Includes efficient iterative algorithmic solutions for inference, optimization, and satisfaction problems through message passing Shows applications in areas such as wireless communications and computer vision.
Electrical engineering. --- Signal processing. --- Image processing. --- Speech processing systems. --- Computer communication systems. --- Communications Engineering, Networks. --- Signal, Image and Speech Processing. --- Computer Communication Networks. --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Electronic data processing --- Network computers --- Computational linguistics --- Information theory --- Modulation theory --- Oral communication --- Speech --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Electric engineering --- Engineering --- Distributed processing --- Telecommunication. --- Computer networks. --- Signal, Speech and Image Processing . --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Telecommunications --- Communication --- Telecommuting
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This book takes a comprehensive study on turbo message passing algorithms for structured signal recovery, where the considered structured signals include 1) a sparse vector/matrix (which corresponds to the compressed sensing (CS) problem), 2) a low-rank matrix (which corresponds to the affine rank minimization (ARM) problem), 3) a mixture of a sparse matrix and a low-rank matrix (which corresponds to the robust principal component analysis (RPCA) problem). The book is divided into three parts. First, the authors introduce a turbo message passing algorithm termed denoising-based Turbo-CS (D-Turbo-CS). Second, the authors introduce a turbo message passing (TMP) algorithm for solving the ARM problem. Third, the authors introduce a TMP algorithm for solving the RPCA problem which aims to recover a low-rank matrix and a sparse matrix from their compressed mixture. With this book, we wish to spur new researches on applying message passing to various inference problems. Provides an in depth look into turbo message passing algorithms for structured signal recovery Includes efficient iterative algorithmic solutions for inference, optimization, and satisfaction problems through message passing Shows applications in areas such as wireless communications and computer vision.
Electronics --- Electrical engineering --- Applied physical engineering --- Engineering sciences. Technology --- Computer architecture. Operating systems --- Computer. Automation --- DIP (documentimage processing) --- digitale signaalverwerking --- beeldverwerking --- spraaktechnologie --- signal processing --- computernetwerken --- elektrotechniek --- signaalprocessoren --- signaalverwerking
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Electronics --- Electrical engineering --- Applied physical engineering --- Engineering sciences. Technology --- Computer architecture. Operating systems --- Computer. Automation --- DIP (documentimage processing) --- digitale signaalverwerking --- beeldverwerking --- spraaktechnologie --- signal processing --- computernetwerken --- elektrotechniek --- signaalprocessoren --- signaalverwerking
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This book provides an overview of the impact of the pandemic in China and the USA and presents a research agenda for use, access, and adoption of information and communication technologies (ICT) in the era of COVID-19. The global COVID-19 pandemic changed lives overnight and exposed socially vulnerable populations to ever-challenging situations. One significant challenge was the use, access, and adoption of technological resources. To understand how socially vulnerable populations managed the COVID-19 pandemic and adapt to the new normal, it is important for researchers and practitioners to identify the challenges and understand the perceptions of technologies. Through various research studies, this edited volume addresses the impact of the global COVID-19 pandemic and the adoption of technologies (from artificial intelligence to telehealth and telecommunications) among some socially vulnerable populations (including children, older adults, COVID-19 patients, and general marginalized populations) in the world. The information divide faced by socially vulnerable groups is studied as well as the dimension of vulnerabilities and the impacts of specific technologies.
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This book focuses on the model and algorithm aspects of securing Unmanned Aerial Vehicle Networks (UAV). To equip readers with the essential knowledge required for conducting research in this field, it covers the foundational concepts of this topic as well. This book also offers a detailed insight into UAV networks from the physical layer security point of view. The authors discuss the appropriate channel models for characterizing various propagation environments that UAV networks are exposed. The state-of-the-art technologies, such as UAV trajectory design, cooperative jamming and reconfigurable intelligent surfaces are covered. The corresponding algorithms for significantly improving the security of UAV networks, along with practical case studies on topics such as energy-efficient and secure UAV networks, elevation angle-distance trade-off for securing UAV networks and securing UAV networks with the aid of reconfigurable intelligent surfaces are presented as well. Last, this book outlines the future challenges and research directions to facilitate further studies on secure UAV networks. This book is suitable reading for graduate students and researchers who are interested in the research areas of UAV networking and communications, IoT security, and physical layer security in wireless networks. Professionals working within these related fields will also benefit from this book. .
Computer networks. --- Wireless communication systems. --- Mobile communication systems. --- Computer networks --- Telecommunication. --- Computer Communication Networks. --- Wireless and Mobile Communication. --- Mobile and Network Security. --- Communications Engineering, Networks. --- Security measures. --- Drone aircraft
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"Focused on the United States, this book summarizes the secondary impacts of COVID-19 due to the increased use of technology. Establishing the global response of social distancing, mandates for non-essential business, and working from home, the book centers on the disparate guidance provided at the State and local levels, domestically. Marginalized populations are highlighted to identify areas where technology facilitated access and reach or contributed to difficulties catapulted by digital literacy or digital access issues. To explain how people may have been empowered or left behind due to new and unique reliance on technology, this book is structured based on the Social Determinants of Health domains. Specifically, this book explains how technology was an umbrella domain, impacting every aspect of life during the pandemic, and included access, use, adoption, digital literacy, digital equity, as well as privacy and security concerns. Given this book's focus on the impacts to marginalized populations, there is a thread throughout the book related to the use of technology to perpetuate hate, discrimination, racism, and xenophobic behaviors that emerged as a twin pandemic during COVID. Part I explains the defining differences between primary and secondary impacts, as well as the unique guidelines adopted in each state. Part II of the book is focused on specific domains, where each chapter is dedicated to topics including economic stability through employment, education, healthcare, and the social/community context through access to services. Part III focuses on unique technological considerations related to COVID-19 such as mobile health related apps and privacy or security issues that may pose barriers to the adoption and use of technology. Finally, the book ends with a conclusion chapter, which explicitly explains the advantages and disadvantages of technology adoption during COVID-19. These exposed benefits and challenges will have implications for policies, disaster management practices, and interdisciplinary research"--
COVID-19 Pandemic, 2020-2023 --- COVID-19 Pandemic, 2020-2023 --- Computer literacy --- Influence. --- Social aspects. --- Social aspects.
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This Springerbreif introduces a threshold-based channel sparsification approach, and then, the sparsity is exploited for scalable channel training. Last but not least, this brief introduces two scalable cooperative signal detection algorithms in C-RANs. The authors wish to spur new research activities in the following important question: how to leverage the revolutionary architecture of C-RAN to attain unprecedented system capacity at an affordable cost and complexity. Cloud radio access network (C-RAN) is a novel mobile network architecture that has a lot of significance in future wireless networks like 5G. the high density of remote radio heads in C-RANs leads to severe scalability issues in terms of computational and implementation complexities. This Springerbrief undertakes a comprehensive study on scalable signal processing for C-RANs, where ‘scalable’ means that the computational and implementation complexities do not grow rapidly with the network size. This Springerbrief will be target researchers and professionals working in the Cloud Radio Access Network (C-Ran) field, as well as advanced-level students studying electrical engineering.
Signal processing. --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Wireless communication systems. --- Mobile communication systems. --- Telecommunication. --- Wireless and Mobile Communication. --- Signal, Image and Speech Processing. --- Communications Engineering, Networks. --- Electric communication --- Mass communication --- Telecom --- Telecommunication industry --- Telecommunications --- Communication --- Information theory --- Telecommuting --- Vehicles --- Vehicular communication systems --- Radio --- Wireless communication systems --- Communication systems, Wireless --- Wireless data communication systems --- Wireless information networks --- Wireless telecommunication systems --- Telecommunication systems --- Communication systems --- Image processing. --- Speech processing systems. --- Electrical engineering. --- Electric engineering --- Engineering --- Computational linguistics --- Electronic systems --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing
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