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Author: Markus Leinonen
Publisher:
Published: 2019-11-29
Total Pages: 310
ISBN-13: 9781680836462
DOWNLOAD EBOOK →This monograph reviews several recent compressed sensing 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.
Author: Zhu Han
Publisher: Cambridge University Press
Published: 2013-06-06
Total Pages: 308
ISBN-13: 1107018838
DOWNLOAD EBOOK →This comprehensive reference delivers the understanding and skills needed to take advantage of compressive sensing in wireless networks.
Author: Norma Aurea Rangel-Vázquez
Publisher: River Publishers
Published: 2016-09-30
Total Pages: 184
ISBN-13: 8793379854
DOWNLOAD EBOOK →Computational chemistry is a science that allows researchers to study, characterize and predict the structure and stability of chemical systems. In other words: studying energy differences between different states to explain spectroscopic properties and reaction mechanisms at the atomic level. This field is gaining in relevance and strength due to field applications from chemical engineering, electrical engineering, electronics, biomedicine, biology, materials science, to name but a few. Structural Analysis using Computational Chemistry arises from the need to present the progress of computational chemistry in various application areas. Technical topics discussed in the book include: Quantum mechanics and structural molecular study (AM1)Application of quantum models in molecular analysisMolecular analysis of insulin through controlled adsorption in hydrogels based on chitosanAnalysis and molecular characterization of organic materials for application in solar cellsDetermination of thermodynamic properties of ionic liquids through molecular simulation
Author: Radha Sankararajan
Publisher: CRC Press
Published: 2022-09-01
Total Pages: 493
ISBN-13: 1000794369
DOWNLOAD EBOOK →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.
Author: Malek Benslama
Publisher: Elsevier
Published: 2017-11-20
Total Pages: 257
ISBN-13: 0081019688
DOWNLOAD EBOOK →Compressed Sensing in Li-Fi and Wi-Fi Networks features coverage of the first applications in optical telecommunications and wireless. After extensive development of basic theory, many techniques are presented, such as non-asymptotic analysis of random matrices, adaptive detection, greedy algorithms, and the use of graphical models. The book can be used as a comprehensive manual for teaching and research in courses covering advanced signal processing, efficient data processing algorithms, and telecommunications. After a thorough review of the basic theory of compressed sensing, many mathematical techniques are presented, including advanced signal modeling, Nyquist sub-sampling of analog signals, the non-asymptotic analysis of random matrices, adaptive detection, greedy algorithms, and the use of graphical models. Offers extensive development of basic theory behind telecommunications and wireless networks Contains broad coverage of treat compressed sensing, including electromagnetism signals Provides insights into the two key areas of telecommunications, WIFI and LIFI Includes information on advanced signal modeling, Nyquist sub-sampling of analog signals, the non-asymptotic analysis of random matrices, adaptive detection, greedy algorithms, and more
Author: Philipp Walk
Publisher: Springer
Published: 2018-10-11
Total Pages:
ISBN-13: 9789811065408
DOWNLOAD EBOOK →This textbook focuses on applications of compressed sensing (CS) and sub-Nyquist sampling techniques to wireless communications such as multi-carrier, IMIMO, UWB, LTE, 5G, Internet of Things, and machine learning. Written for an engineering audience, the book is presented in a strictly mathematical manner, and to keep it self-contained and accessible to engineering students it explains all the mathematical tools used. It also develops a generalization of CS to more structured signal models, which is necessary in order to apply CS to digital communication. The work is based on research material collected by the authors over recent years.
Author: Yue Gao
Publisher: Springer
Published: 2018-10-19
Total Pages: 93
ISBN-13: 303000290X
DOWNLOAD EBOOK →This SpringerBrief discusses the applications of spare representation in wireless communications, with a particular focus on the most recent developed compressive sensing (CS) enabled approaches. With the help of sparsity property, sub-Nyquist sampling can be achieved in wideband cognitive radio networks by adopting compressive sensing, which is illustrated in this brief, and it starts with a comprehensive overview of compressive sensing principles. Subsequently, the authors present a complete framework for data-driven compressive spectrum sensing in cognitive radio networks, which guarantees robustness, low-complexity, and security. Particularly, robust compressive spectrum sensing, low-complexity compressive spectrum sensing, and secure compressive sensing based malicious user detection are proposed to address the various issues in wideband cognitive radio networks. Correspondingly, the real-world signals and data collected by experiments carried out during TV white space pilot trial enables data-driven compressive spectrum sensing. The collected data are analysed and used to verify our designs and provide significant insights on the potential of applying compressive sensing to wideband spectrum sensing. This SpringerBrief provides readers a clear picture on how to exploit the compressive sensing to process wireless signals in wideband cognitive radio networks. Students, professors, researchers, scientists, practitioners, and engineers working in the fields of compressive sensing in wireless communications will find this SpringerBrief very useful as a short reference or study guide book. Industry managers, and government research agency employees also working in the fields of compressive sensing in wireless communications will find this SpringerBrief useful as well.
Author: Xianjun Yang
Publisher:
Published: 2015
Total Pages: 163
ISBN-13:
DOWNLOAD EBOOK →Compressed sensing (CS) suggests that it is possible to enable sub-Nyquist sampling, by merging sampling and compression into one single step. Hence, CS will lead to a revolution in the sampling area. Moreover, CS will have great impacts on information theory, coding and wireless communications. In this thesis, we will study the basic sampling problem of analog sparse signals and investigate the applications of CS into cognitive radio networks (CRNs) and wiresless sensor networks (WSNs).
Author: Giulio Coluccia
Publisher: Springer
Published: 2015-05-29
Total Pages: 104
ISBN-13: 9812873902
DOWNLOAD EBOOK →This book presents a survey of the state-of-the art in the exciting and timely topic of compressed sensing for distributed systems. It has to be noted that, while compressed sensing has been studied for some time now, its distributed applications are relatively new. Remarkably, such applications are ideally suited to exploit all the benefits that compressed sensing can provide. The objective of this book is to provide the reader with a comprehensive survey of this topic, from the basic concepts to different classes of centralized and distributed reconstruction algorithms, as well as a comparison of these techniques. This book collects different contributions on these aspects. It presents the underlying theory in a complete and unified way for the first time, presenting various signal models and their use cases. It contains a theoretical part collecting latest results in rate-distortion analysis of distributed compressed sensing, as well as practical implementations of algorithms obtaining performance close to the theoretical bounds. It presents and discusses various distributed reconstruction algorithms, summarizing the theoretical reconstruction guarantees and providing a comparative analysis of their performance and complexity. In summary, this book will allow the reader to get started in the field of distributed compressed sensing from theory to practice. We believe that this book can find a broad audience among researchers, scientists, or engineers with very diverse backgrounds, having interests in mathematical optimization, network systems, graph theoretical methods, linear systems, stochastic systems, and randomized algorithms. To help the reader become familiar with the theory and algorithms presented, accompanying software is made available on the authors’ web site, implementing several of the algorithms described in the book. The only background required of the reader is a good knowledge of advanced calculus and linear algebra.
Author: Zhu Han
Publisher: Cambridge University Press
Published: 2013-06-06
Total Pages: 308
ISBN-13: 1107328462
DOWNLOAD EBOOK →Compressive sensing is a new signal processing paradigm that aims to encode sparse signals by using far lower sampling rates than those in the traditional Nyquist approach. It helps acquire, store, fuse and process large data sets efficiently and accurately. This method, which links data acquisition, compression, dimensionality reduction and optimization, has attracted significant attention from researchers and engineers in various areas. This comprehensive reference develops a unified view on how to incorporate efficiently the idea of compressive sensing over assorted wireless network scenarios, interweaving concepts from signal processing, optimization, information theory, communications and networking to address the issues in question from an engineering perspective. It enables students, researchers and communications engineers to develop a working knowledge of compressive sensing, including background on the basics of compressive sensing theory, an understanding of its benefits and limitations, and the skills needed to take advantage of compressive sensing in wireless networks.
