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2009
IEEE

Adaptive distributed transforms for irregularly sampled Wireless Sensor Networks

10 years 4 months ago
Adaptive distributed transforms for irregularly sampled Wireless Sensor Networks
We develop energy-efficient, adaptive distributed transforms for data gathering in wireless sensor networks. In particular, we consider a class of unidirectional transforms that are computed as data is forwarded to the sink along a given routing tree and develop a tree-based Karhunen-Lo`eve Transform (KLT) that is optimal in that it achieves maximum data de-correlation among this class of transforms. As an alternative to this KLT (which incurs communication overhead in order to learn second order data statistics), we propose a backward adaptive filter optimization algorithm for distributed wavelet transforms that i) achieves near optimal performance and ii) has no communication overhead in learning statistics.
Godwin Shen, Sunil K. Narang, Antonio Ortega
Added 21 May 2010
Updated 21 May 2010
Type Conference
Year 2009
Where ICASSP
Authors Godwin Shen, Sunil K. Narang, Antonio Ortega
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