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- Author: Sundeep Prabhakar Chepuri
- Publisher: Now Publishers
- Year: 2016
- ISBN-10: 1680832360
- ISBN-13: 9781680832365
- Format: 15.6 x 23.4 x 0.9 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
Sparse Sensing for Statistical Inference (e-book) (used book) | bookbook.eu
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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.
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- Author: Sundeep Prabhakar Chepuri
- Publisher: Now Publishers
- Year: 2016
- ISBN-10: 1680832360
- ISBN-13: 9781680832365
- Format: 15.6 x 23.4 x 0.9 cm, softcover
- Language: English English
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.
Reviews