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This unique text helps make sense of big data in engineering applications using tools and techniques from signal processing. It presents fundamental signal processing theories and software implementations, reviews current research trends and challenges, and describes the techniques used for analysis, design and optimization. Readers will learn about key theoretical issues such as data modelling and representation, scalable and low-complexity information processing and optimization, tensor and sublinear algorithms, and deep learning and software architecture, and their application to a wide range of engineering scenarios. Applications discussed in detail include wireless networking, smart grid systems, and sensor networks and cloud computing. This is the ideal text for researchers and practising engineers wanting to solve practical problems involving large amounts of data, and for students looking to grasp the fundamentals of big data analytics.
Book Synopsis Signal Processing and Networking for Big Data Applications by : Zhu Han
Download or read book Signal Processing and Networking for Big Data Applications written by Zhu Han and published by Cambridge University Press. This book was released on 2017-04-27 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique text helps make sense of big data in engineering applications using tools and techniques from signal processing. It presents fundamental signal processing theories and software implementations, reviews current research trends and challenges, and describes the techniques used for analysis, design and optimization. Readers will learn about key theoretical issues such as data modelling and representation, scalable and low-complexity information processing and optimization, tensor and sublinear algorithms, and deep learning and software architecture, and their application to a wide range of engineering scenarios. Applications discussed in detail include wireless networking, smart grid systems, and sensor networks and cloud computing. This is the ideal text for researchers and practising engineers wanting to solve practical problems involving large amounts of data, and for students looking to grasp the fundamentals of big data analytics.
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.
Book Synopsis Sublinear Algorithms for Big Data Applications by : Dan Wang
Download or read book Sublinear Algorithms for Big Data Applications written by Dan Wang and published by Springer. This book was released on 2015-07-16 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
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. Presents the first book on cooperative signal processing and graph signal processing Provides a range of applications and application areas that are thoroughly covered Includes an editor in chief and associate editor from the IEEE Transactions on Signal Processing and Information Processing over Networks who have recruited top contributors for the book
Book Synopsis Cooperative and Graph Signal Processing by : Petar Djuric
Download or read book Cooperative and Graph Signal Processing written by Petar Djuric and published by Academic Press. This book was released on 2018-07-04 with total page 866 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Presents the first book on cooperative signal processing and graph signal processing Provides a range of applications and application areas that are thoroughly covered Includes an editor in chief and associate editor from the IEEE Transactions on Signal Processing and Information Processing over Networks who have recruited top contributors for the book
This book collects selected papers from the 7th Conference on Signal and Information Processing, Networking and Computers held in Rizhao, China, on September 21-23, 2020. The 7th International Conference on Signal and Information Processing, Networking and Computers (ICSINC) was held in Rizhao, China, on September 21-23, 2020.
Book Synopsis Signal and Information Processing, Networking and Computers by : Yue Wang
Download or read book Signal and Information Processing, Networking and Computers written by Yue Wang and published by Springer Nature. This book was released on 2020-12-17 with total page 1104 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects selected papers from the 7th Conference on Signal and Information Processing, Networking and Computers held in Rizhao, China, on September 21-23, 2020. The 7th International Conference on Signal and Information Processing, Networking and Computers (ICSINC) was held in Rizhao, China, on September 21-23, 2020.
This proceedings book presents selected papers from the 5th Conference on Signal and Information Processing, Networking and Computers (ICSINC), held in Yuzhou, China, from November 29 to December 1, 2018. It focuses on the current research in a wide range of areas in the fields of information theory, communication systems, computer science, signal processing, aerospace technologies, and other related technologies. With contributions from experts from both academia and industry, it is a valuable resource for anyone who is interested in this field.
Book Synopsis Signal and Information Processing, Networking and Computers by : Songlin Sun
Download or read book Signal and Information Processing, Networking and Computers written by Songlin Sun and published by Springer. This book was released on 2019-04-16 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings book presents selected papers from the 5th Conference on Signal and Information Processing, Networking and Computers (ICSINC), held in Yuzhou, China, from November 29 to December 1, 2018. It focuses on the current research in a wide range of areas in the fields of information theory, communication systems, computer science, signal processing, aerospace technologies, and other related technologies. With contributions from experts from both academia and industry, it is a valuable resource for anyone who is interested in this field.
This book presents state-of-the-art solutions to the theoretical and practical challenges stemming from the leverage of big data and its computational intelligence in supporting smart network operation, management, and optimization. In particular, the technical focus covers the comprehensive understanding of network big data, efficient collection and management of network big data, distributed and scalable online analytics for network big data, and emerging applications of network big data for computational intelligence.
Book Synopsis Big Data and Computational Intelligence in Networking by : Yulei Wu
Download or read book Big Data and Computational Intelligence in Networking written by Yulei Wu and published by CRC Press. This book was released on 2017-12-14 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents state-of-the-art solutions to the theoretical and practical challenges stemming from the leverage of big data and its computational intelligence in supporting smart network operation, management, and optimization. In particular, the technical focus covers the comprehensive understanding of network big data, efficient collection and management of network big data, distributed and scalable online analytics for network big data, and emerging applications of network big data for computational intelligence.
Utilising both key mathematical tools and state-of-the-art research results, this text explores the principles underpinning large-scale information processing over networks and examines the crucial interaction between big data and its associated communication, social and biological networks. Written by experts in the diverse fields of machine learning, optimisation, statistics, signal processing, networking, communications, sociology and biology, this book employs two complementary approaches: first analysing how the underlying network constrains the upper-layer of collaborative big data processing, and second, examining how big data processing may boost performance in various networks. Unifying the broad scope of the book is the rigorous mathematical treatment of the subjects, which is enriched by in-depth discussion of future directions and numerous open-ended problems that conclude each chapter. Readers will be able to master the fundamental principles for dealing with big data over large systems, making it essential reading for graduate students, scientific researchers and industry practitioners alike.
Book Synopsis Big Data over Networks by : Shuguang Cui
Download or read book Big Data over Networks written by Shuguang Cui and published by Cambridge University Press. This book was released on 2016-01-14 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: Utilising both key mathematical tools and state-of-the-art research results, this text explores the principles underpinning large-scale information processing over networks and examines the crucial interaction between big data and its associated communication, social and biological networks. Written by experts in the diverse fields of machine learning, optimisation, statistics, signal processing, networking, communications, sociology and biology, this book employs two complementary approaches: first analysing how the underlying network constrains the upper-layer of collaborative big data processing, and second, examining how big data processing may boost performance in various networks. Unifying the broad scope of the book is the rigorous mathematical treatment of the subjects, which is enriched by in-depth discussion of future directions and numerous open-ended problems that conclude each chapter. Readers will be able to master the fundamental principles for dealing with big data over large systems, making it essential reading for graduate students, scientific researchers and industry practitioners alike.
This book reviews the state of the art in big data analysis and networks technologies. It addresses a range of issues that pertain to: signal processing, probability models, machine learning, data mining, databases, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart cities, networks technologies, etc. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. In turn, data science inspires novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and the social sciences. All papers presented here are the product of extensive field research involving applications and techniques related to data analysis in general, and to big data and networks technologies in particular. Given its scope, the book will appeal to advanced undergraduate and graduate students, postdoctoral researchers, lecturers and industrial researchers, as well general readers interested in big data analysis and networks technologies.
Book Synopsis Big Data and Networks Technologies by : Yousef Farhaoui
Download or read book Big Data and Networks Technologies written by Yousef Farhaoui and published by Springer. This book was released on 2019-07-17 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in big data analysis and networks technologies. It addresses a range of issues that pertain to: signal processing, probability models, machine learning, data mining, databases, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart cities, networks technologies, etc. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. In turn, data science inspires novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and the social sciences. All papers presented here are the product of extensive field research involving applications and techniques related to data analysis in general, and to big data and networks technologies in particular. Given its scope, the book will appeal to advanced undergraduate and graduate students, postdoctoral researchers, lecturers and industrial researchers, as well general readers interested in big data analysis and networks technologies.
A comprehensive and invaluable guide to 5G technology, implementation and practice in one single volume. For all things 5G, this book is a must-read. Signal processing techniques have played the most important role in wireless communications since the second generation of cellular systems. It is anticipated that new techniques employed in 5G wireless networks will not only improve peak service rates significantly, but also enhance capacity, coverage, reliability , low-latency, efficiency, flexibility, compatibility and convergence to meet the increasing demands imposed by applications such as big data, cloud service, machine-to-machine (M2M) and mission-critical communications. This book is a comprehensive and detailed guide to all signal processing techniques employed in 5G wireless networks. Uniquely organized into four categories, New Modulation and Coding, New Spatial Processing, New Spectrum Opportunities and New System-level Enabling Technologies, it covers everything from network architecture, physical-layer (down-link and up-link), protocols and air interface, to cell acquisition, scheduling and rate adaption, access procedures and relaying to spectrum allocations. All technology aspects and major roadmaps of global 5G standard development and deployments are included in the book. Key Features: Offers step-by-step guidance on bringing 5G technology into practice, by applying algorithms and design methodology to real-time circuit implementation, taking into account rapidly growing applications that have multi-standards and multi-systems. Addresses spatial signal processing for 5G, in particular massive multiple-input multiple-output (massive-MIMO), FD-MIMO and 3D-MIMO along with orbital angular momentum multiplexing, 3D beamforming and diversity. Provides detailed algorithms and implementations, and compares all multicarrier modulation and multiple access schemes that offer superior data transmission performance including FBMC, GFDM, F-OFDM, UFMC, SEFDM, FTN, MUSA, SCMA and NOMA. Demonstrates the translation of signal processing theories into practical solutions for new spectrum opportunities in terms of millimeter wave, full-duplex transmission and license assisted access. Presents well-designed implementation examples, from individual function block to system level for effective and accurate learning. Covers signal processing aspects of emerging system and network architectures, including ultra-dense networks (UDN), software-defined networks (SDN), device-to-device (D2D) communications and cloud radio access network (C-RAN).
Book Synopsis Signal Processing for 5G by : Fa-Long Luo
Download or read book Signal Processing for 5G written by Fa-Long Luo and published by John Wiley & Sons. This book was released on 2016-10-17 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and invaluable guide to 5G technology, implementation and practice in one single volume. For all things 5G, this book is a must-read. Signal processing techniques have played the most important role in wireless communications since the second generation of cellular systems. It is anticipated that new techniques employed in 5G wireless networks will not only improve peak service rates significantly, but also enhance capacity, coverage, reliability , low-latency, efficiency, flexibility, compatibility and convergence to meet the increasing demands imposed by applications such as big data, cloud service, machine-to-machine (M2M) and mission-critical communications. This book is a comprehensive and detailed guide to all signal processing techniques employed in 5G wireless networks. Uniquely organized into four categories, New Modulation and Coding, New Spatial Processing, New Spectrum Opportunities and New System-level Enabling Technologies, it covers everything from network architecture, physical-layer (down-link and up-link), protocols and air interface, to cell acquisition, scheduling and rate adaption, access procedures and relaying to spectrum allocations. All technology aspects and major roadmaps of global 5G standard development and deployments are included in the book. Key Features: Offers step-by-step guidance on bringing 5G technology into practice, by applying algorithms and design methodology to real-time circuit implementation, taking into account rapidly growing applications that have multi-standards and multi-systems. Addresses spatial signal processing for 5G, in particular massive multiple-input multiple-output (massive-MIMO), FD-MIMO and 3D-MIMO along with orbital angular momentum multiplexing, 3D beamforming and diversity. Provides detailed algorithms and implementations, and compares all multicarrier modulation and multiple access schemes that offer superior data transmission performance including FBMC, GFDM, F-OFDM, UFMC, SEFDM, FTN, MUSA, SCMA and NOMA. Demonstrates the translation of signal processing theories into practical solutions for new spectrum opportunities in terms of millimeter wave, full-duplex transmission and license assisted access. Presents well-designed implementation examples, from individual function block to system level for effective and accurate learning. Covers signal processing aspects of emerging system and network architectures, including ultra-dense networks (UDN), software-defined networks (SDN), device-to-device (D2D) communications and cloud radio access network (C-RAN).
Book Synopsis Signal and Information Processing, Networking and Computers by : Yue Wang
Download or read book Signal and Information Processing, Networking and Computers written by Yue Wang and published by Springer Nature. This book was released on with total page 537 pages. Available in PDF, EPUB and Kindle. Book excerpt:
