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Compressive Sensing (CS) is a recently developed mechanism that allows signal acquisition and compression to be performed in one inexpensive step so that the sampling process itself produces a compressed version of the signal. This significantly improves systemic energy efficiency because the average sampling rate can be considerably reduced and explicit compression eliminated. In this paper, we introduce a modification to the canonical CS recovery technique that enables even higher gains for event detection applications. We show a practical implementation of this compressive detection with energy constrained wireless sensor nodes and quantify the gains accrued through simulation and experimentation. <br> <hr> <a href=http://nesl.ee.ucla.edu/fw/zainul/ISLPED-WBPcode.zip>Source Code</a> <hr>
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