| Sparse Sensing for Statistical Inference Contributor(s): Chepuri, Sundeep Prabhakar (Author), Leus, Geert (Author) |
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ISBN: 1680832360 ISBN-13: 9781680832365 Publisher: Now Publishers OUR PRICE: $94.05 Product Type: Paperback - Other Formats Published: December 2016 |
| Additional Information |
| BISAC Categories: - Technology & Engineering | Signals & Signal Processing |
| Series: Foundations and Trends(r) in Signal Processing |
| Physical Information: 0.37" H x 6.14" W x 9.21" (0.55 lbs) 172 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: Sensors 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. |