Computer Science – Distributed – Parallel – and Cluster Computing
Scientific paper
2011-05-10
Computer Science
Distributed, Parallel, and Cluster Computing
8 pages, 5 figures, to appear in the Proceedings of the IEEE International Conference on Distributed Computing in Sensor Syste
Scientific paper
Unions of graph Fourier multipliers are an important class of linear operators for processing signals defined on graphs. We present a novel method to efficiently distribute the application of these operators to the high-dimensional signals collected by sensor networks. The proposed method features approximations of the graph Fourier multipliers by shifted Chebyshev polynomials, whose recurrence relations make them readily amenable to distributed computation. We demonstrate how the proposed method can be used in a distributed denoising task, and show that the communication requirements of the method scale gracefully with the size of the network.
Frossard Pascal
Shuman David I.
Vandergheynst Pierre
No associations
LandOfFree
Chebyshev Polynomial Approximation for Distributed Signal Processing does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Chebyshev Polynomial Approximation for Distributed Signal Processing, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Chebyshev Polynomial Approximation for Distributed Signal Processing will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-279036