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In this work we consider the design of the lifting filters and trees used in a separable tree-based wavelet transform. We first consider the use of improved prediction filters, optimized to represent more efficiently smooth signals for arbitrary tree structures. We then consider the design of update filters that are orthogonal to neighboring prediction operators. While the corresponding decomposition...
This work presents a class of unidirectional lifting-based wavelet transforms for an arbitrary communication graph in a wireless sensor network. These transforms are unidirectional in the sense that they are computed as data is forwarded towards the sink on a routing tree. We derive a set of conditions under which a lifting transform is unidirectional, then find the full set of those transforms. Among...
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-Loeve Transform (KLT) that is optimal in that it achieves maximum data de-correlation among this class of transforms...
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