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Multiresolution graph signal processing via circulant structures

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4 Author(s)
Ekambaram, V.N. ; Dept. of EECS, UC Berkeley, Berkeley, CA, USA ; Fanti, G.C. ; Ayazifar, B. ; Ramchandran, K.

We use circulant structures to present a new framework for multiresolution analysis and processing of graph signals. Among the essential features of circulant graphs is that they accommodate fundamental signal processing operations, such as linear shift-invariant filtering, downsampling, upsampling, and reconstruction-features that offer substantial advantage. We design two-channel, critically-sampled, perfect-reconstruction, orthogonal lattice-filter structures to process signals defined on circulant graphs. To extend our reach to noncirculant graphs, we present a method to decompose a connected, undirected graph into a combination of circulant graphs. To evaluate our proposed framework, we offer examples of synthetic and real-world graph signal data and their multiscale decompositions.

Published in:

Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE), 2013 IEEE

Date of Conference:

11-14 Aug. 2013

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