Download or read book Compressive Sensing for Wireless Communication written by Radha Sankararajan and published by CRC Press. This book was released on 2022-09-01 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Structural Analysis using Computational Chemistry written by Norma Aurea Rangel-Vázquez and published by River Publishers. This book was released on 2016-09-30 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Compressive Sensing for Wireless Networks written by Zhu Han and published by Cambridge University Press. This book was released on 2013-06-06 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive reference delivers the understanding and skills needed to take advantage of compressive sensing in wireless networks.
Download or read book Data Driven Wireless Networks written by Yue Gao and published by Springer. This book was released on 2018-10-19 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Compressed Sensing with Applications in Wireless Networks written by Markus Leinonen and published by . This book was released on 2019-11-29 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Compressive Sensing in Wireless Communications written by Jia Meng and published by . This book was released on 2010 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Mathematical Methods in Imaging written by Otmar Scherzer and published by Springer Science & Business Media. This book was released on 2010-11-23 with total page 1626 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 150 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and computer scientists working in imaging will also find this handbook useful.
Download or read book Compressive Sensing Models and Algorithms for Wireless Communication Systems written by Feibai Zhu and published by . This book was released on 2018 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Mathematical Introduction to Compressive Sensing written by Simon Foucart and published by Springer Science & Business Media. This book was released on 2013-08-13 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: At the intersection of mathematics, engineering, and computer science sits the thriving field of compressive sensing. Based on the premise that data acquisition and compression can be performed simultaneously, compressive sensing finds applications in imaging, signal processing, and many other domains. In the areas of applied mathematics, electrical engineering, and theoretical computer science, an explosion of research activity has already followed the theoretical results that highlighted the efficiency of the basic principles. The elegant ideas behind these principles are also of independent interest to pure mathematicians. A Mathematical Introduction to Compressive Sensing gives a detailed account of the core theory upon which the field is build. With only moderate prerequisites, it is an excellent textbook for graduate courses in mathematics, engineering, and computer science. It also serves as a reliable resource for practitioners and researchers in these disciplines who want to acquire a careful understanding of the subject. A Mathematical Introduction to Compressive Sensing uses a mathematical perspective to present the core of the theory underlying compressive sensing.
Download or read book Compressive Sensing in Healthcare written by Mahdi Khosravy and published by Academic Press. This book was released on 2020-05-18 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Compressive Sensing in Healthcare, part of the Advances in Ubiquitous Sensing Applications for Healthcare series gives a review on compressive sensing techniques in a practical way, also presenting deterministic compressive sensing techniques that can be used in the field. The focus of the book is on healthcare applications for this technology. It is intended for both the creators of this technology and the end users of these products. The content includes the use of EEG and ECG, plus hardware and software requirements for building projects. Body area networks and body sensor networks are explored. Provides a toolbox for compressive sensing in health, presenting both mathematical and coding information Presents an intuitive introduction to compressive sensing, including MATLAB tutorials Covers applications of compressive sensing in health care
Download or read book Compressed Sensing in Li Fi and Wi Fi Networks written by Malek Benslama and published by Elsevier. This book was released on 2017-11-20 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Compressive Sensing for Wireless and Sensor Systems written by Ji Wu and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Compressive sensing (CS) is an emerging field based on the revelation that a small collection of linear projections of a sparse signal contains enough information for stable, sub-Nyquist signal acquisition. It provides a potential way to acquire the sparse data efficiently, or equivalently, highly accurate recovery of sparse data from undersampled measurements. Huffman coding and compressive sensing are adopted to compress real-world wind tunnel data. Both uniform and non-uniform Huffman coding are evaluated in terms of the number of quantization levels, mean square error, codeword length and compression ratio. The main drawback of Huffman coding is that it requires calculating the probability of each symbol before encoding. It means it may not be appropriate for real-time compression. We applied CS to wind tunnel data and compared its performance against the theoretical error bound.Due to limited energy and physical size of the sensor nodes, the conventional security mechanisms with high computation complexity are not feasible for wireless sensor networks (WSNs). A compressive sensing-based encryption is proposed for distributed WSNs, which provide both signal compression and encryption guarantees, without the additional computational cost of a separate encryption protocol. The computational and information-theoretical secrecy of the compressive sensing algorithm is also investigated. For the proposed distributed WSNs, if only a fraction of randomizer bits is stored by an eavesdropper, then the eavesdropper cannot obtain any information about the plaintext.We studied a compressive sensing-based Ultra-WideBand (UWB) wireless communication system. Compared with the conventional UWB system, it can jointly estimate the channel and compress the data. No information about the transmitted signal is required in advance as long as the channel follows the autoregressive model. The performance of compressive sensing-based data encryption scheme shows that the original data could never be reconstructed when the measurement matrix is not available. Hence, compressive sensing can be implemented as a data encryption scheme with good secrecy.
Download or read book When Compressive Sensing Meets Mobile Crowdsensing written by Linghe Kong and published by Springer. This book was released on 2019-06-08 with total page 127 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive introduction to applying compressive sensing to improve data quality in the context of mobile crowdsensing. It addresses the following main topics: recovering missing data, efficiently collecting data, preserving user privacy, and detecting false data. Mobile crowdsensing, as an emerging sensing paradigm, enables the masses to take part in data collection tasks with the aid of powerful mobile devices. However, mobile crowdsensing platforms have yet to be widely adopted in practice, the major concern being the quality of the data collected. There are numerous causes: some locations may generate redundant data, while others may not be covered at all, since the participants are rarely systematically coordinated; privacy is a concern for some people, who don’t wish to share their real-time locations, and therefore some key information may be missing; further, some participants may upload fake data in order to fraudulently gain rewards. To address these problematic aspects, compressive sensing, which works by accurately recovering a sparse signal using very few samples, has proven to offer an effective solution.
Download or read book Compressed Sensing written by Philipp Walk and published by Springer. This book was released on 2018-10-11 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Compressed Sensing written by Yonina C. Eldar and published by Cambridge University Press. This book was released on 2012-05-17 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: Compressed sensing is an exciting, rapidly growing field, attracting considerable attention in electrical engineering, applied mathematics, statistics and computer science. This book provides the first detailed introduction to the subject, highlighting theoretical advances and a range of applications, as well as outlining numerous remaining research challenges. After a thorough review of the basic theory, many cutting-edge techniques are presented, including advanced signal modeling, sub-Nyquist sampling of analog signals, non-asymptotic analysis of random matrices, adaptive sensing, greedy algorithms and use of graphical models. All chapters are written by leading researchers in the field, and consistent style and notation are utilized throughout. Key background information and clear definitions make this an ideal resource for researchers, graduate students and practitioners wanting to join this exciting research area. It can also serve as a supplementary textbook for courses on computer vision, coding theory, signal processing, image processing and algorithms for efficient data processing.
Download or read book Research on Compressed Sensing and Its Applications in Wireless Communications written by Xianjun Yang and published by . This book was released on 2015 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).
Download or read book Sensing Techniques for Next Generation Cognitive Radio Networks written by Bagwari, Ashish and published by IGI Global. This book was released on 2018-08-30 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: The inadequate use of wireless spectrum resources has recently motivated researchers and practitioners to look for new ways to improve resource efficiency. As a result, new cognitive radio technologies have been proposed as an effective solution. Sensing Techniques for Next Generation Cognitive Radio Networks is a pivotal reference source that provides vital research on the application of spectrum sensing techniques. While highlighting topics such as radio identification, compressive sensing, and wavelet transform, this publication explores the standards and the methods of cognitive radio network architecture. This book is ideally designed for IT and network engineers, practitioners, and researchers seeking current research on radio scene analysis for cognitive radios and networks.
