Compressive Sensing For Wireless And Sensor Systems PDF Download
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| Author | : Norma Aurea Rangel-Vázquez |
| Publisher | : River Publishers |
| Total Pages | : 184 |
| Release | : 2016-09-30 |
| Genre | : Science |
| ISBN | : 8793379854 |
Download Structural Analysis using Computational Chemistry Book in PDF, ePub and Kindle
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 | : Markus Leinonen |
| Publisher | : |
| Total Pages | : 310 |
| Release | : 2019-11-29 |
| Genre | : Technology & Engineering |
| ISBN | : 9781680836462 |
Download Compressed Sensing with Applications in Wireless Networks Book in PDF, ePub and Kindle
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 | : Ji Wu |
| Publisher | : |
| Total Pages | : |
| Release | : 2013 |
| Genre | : |
| ISBN | : |
Download Compressive Sensing for Wireless and Sensor Systems Book in PDF, ePub and Kindle
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.
| Author | : Radha Sankararajan |
| Publisher | : CRC Press |
| Total Pages | : 493 |
| Release | : 2022-09-01 |
| Genre | : Technology & Engineering |
| ISBN | : 1000794369 |
Download Compressive Sensing for Wireless Communication Book in PDF, ePub and Kindle
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 | : Zhu Han |
| Publisher | : Cambridge University Press |
| Total Pages | : 308 |
| Release | : 2013-06-06 |
| Genre | : Computers |
| ISBN | : 1107018838 |
Download Compressive Sensing for Wireless Networks Book in PDF, ePub and Kindle
This comprehensive reference delivers the understanding and skills needed to take advantage of compressive sensing in wireless networks.
| Author | : Wei Chen |
| Publisher | : |
| Total Pages | : |
| Release | : 2013 |
| Genre | : |
| ISBN | : |
Download Compressive Sensing for Wireless Sensor Networks Book in PDF, ePub and Kindle
| Author | : Joachim Ender |
| Publisher | : de Gruyter |
| Total Pages | : 365 |
| Release | : 2016-05-15 |
| Genre | : Mathematics |
| ISBN | : 9783110335316 |
Download Compressive Sensing Book in PDF, ePub and Kindle
Compressive Sensing is a new technique in signal processing, enabling imaging systems with limited capabilities in bandwidth or resolution to recover "natural?" signals with high accuracy. This graduate textbook provides detailed background for study and research in compressive sensing, including signal models, measurement schemes, recovery algorithms, highlighting recent theoretical results and showing a broad range of applications.
| Author | : Bhaskar Krishnamachari |
| Publisher | : Springer |
| Total Pages | : 385 |
| Release | : 2009-06-04 |
| Genre | : Computers |
| ISBN | : 3642020852 |
Download Distributed Computing in Sensor Systems Book in PDF, ePub and Kindle
The book constitutes the refereed proceedings of the Fifth International Conference on Distributed Computing in Sensor Systems, DCOSS 2009, held in Marina del Rey, CA, USA, in June 2009. The 26 revised full papers presented were carefully reviewed and selected from 116 submissions. The research contributions in this proceedings span many aspects of sensor systems, including energy efficient mechanisms, tracking and surveillance, activity recognition, simulation, query optimization, network coding, localization, application development, data and code dissemination.
| Author | : Simon Foucart |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 634 |
| Release | : 2013-08-13 |
| Genre | : Computers |
| ISBN | : 0817649484 |
Download A Mathematical Introduction to Compressive Sensing Book in PDF, ePub and Kindle
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.
| Author | : Fei Hu |
| Publisher | : CRC Press |
| Total Pages | : 676 |
| Release | : 2012-12-15 |
| Genre | : Technology & Engineering |
| ISBN | : 1439892814 |
Download Intelligent Sensor Networks Book in PDF, ePub and Kindle
Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, including compressive sensing and sampling, distributed signal processing, and intelligent signal learning. Presenting recent research results of world-renowned sensing experts, the book is organized into three parts: Machine Learning—describes the application of machine learning and other AI principles in sensor network intelligence—covering smart sensor/transducer architecture and data representation for intelligent sensors Signal Processing—considers the optimization of sensor network performance based on digital signal processing techniques—including cross-layer integration of routing and application-specific signal processing as well as on-board image processing in wireless multimedia sensor networks for intelligent transportation systems Networking—focuses on network protocol design in order to achieve an intelligent sensor networking—covering energy-efficient opportunistic routing protocols for sensor networking and multi-agent-driven wireless sensor cooperation Maintaining a focus on "intelligent" designs, the book details signal processing principles in sensor networks. It elaborates on critical platforms for intelligent sensor networks and illustrates key applications—including target tracking, object identification, and structural health monitoring. It also includes a paradigm for validating the extent of spatiotemporal associations among data sources to enhance data cleaning in sensor networks, a sensor stream reduction application, and also considers the use of Kalman filters for attack detection in a water system sensor network that consists of water level sensors and velocity sensors.
