Enabling Advanced Inference on Sensor Nodes Through Direct Use of Compressively-Sensed Signals

Provided by: edaa
Topic: Big Data
Format: PDF
Now-a-days, sensor networks are being used to monitor increasingly complex physical systems, necessitating advanced signal analysis capabilities as well as the ability to handle large amounts of network data. For the first time, the authors present a methodology to enable advanced decision support on a low power sensor node through the direct use of compressively-sensed signals in a supervised-learning framework; such signals provide a highly efficient means of representing data in the network, and their direct use overcomes the need for energy-intensive signal reconstruction.

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