Title :
Distributed algorithm for graph signal inpainting
Author :
Siheng Chen ; Sandryhaila, Aliaksei ; Kovacevic, Jelena
Author_Institution :
Dept. of ECE, Carnegie Mellon Univ., Pittsburgh, PA, USA
Abstract :
We present a distributed and decentralized algorithm for graph signal inpainting. The previous work obtained a closed-form solution with matrix inversion. In this paper, we ease the computation by using a distributed algorithm, which solves graph signal inpainting by restricting each node to communicate only with its local nodes. We show that the solution of the distributed algorithm converges to the closed-form solution with the corresponding convergence speed. Experiments on online blog classification and temperature prediction suggest that the convergence speed of the proposed distributed algorithm is competitive with that of the centralized algorithm, especially when a graph tends to be regular. Since a distributed algorithm does not require to collect data to a center, it is more practical and efficient.
Keywords :
graph theory; matrix inversion; signal classification; closed-form solution; convergence speed; decentralized algorithm; distributed algorithm; graph signal inpainting; local nodes; matrix inversion; online blog classification; temperature prediction; Blogs; Closed-form solutions; Convergence; Distributed algorithms; Meteorology; Minimization; Signal processing; Signal processing on graphs; distributed computing; graph signal inpainting;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location :
South Brisbane, QLD
DOI :
10.1109/ICASSP.2015.7178668