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OverviewSensors are becoming increasingly omnipresent throughout society. These sensors generate a billion gigabytes of data every day. With the availability of immense computing power at central locations, the local storage and transmission of the data to a central location becomes the bottleneck in the real-time processing of the mass of data. Recently compressed sensing has emerged as a technique to alleviate these problems, but much of the data is blindly discarded without being examined to achieve acceptable throughput rates. Sparse Sensing for Statistical Inference introduces and reviews a new technique called Sparse Sensing that reduces the amount of data that must be collected to start with, proving an efficient and cost-effective method for data collection. This monograph provides the reader with a comprehensive overview of this technique and a framework that can be used by researchers and engineers in implementing the technique in practical sensing systems. Full Product DetailsAuthor: Sundeep Prabhakar Chepuri , Geert LeusPublisher: now publishers Inc Imprint: now publishers Inc Dimensions: Width: 15.60cm , Height: 0.90cm , Length: 23.40cm Weight: 0.251kg ISBN: 9781680832365ISBN 10: 1680832360 Pages: 172 Publication Date: 14 December 2016 Audience: College/higher education , Postgraduate, Research & Scholarly Format: Paperback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents1 Introduction 2 Sparse Sensing 3 Sparse Sensing for Estimation 4 Sparse Sensing for Filtering 5 Sparse Sensing for Detection 6 Continuous Sparse Sensing 7 Outlook ReferencesReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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