Print Email Facebook Twitter Space-shift sampling of graph signals Title Space-shift sampling of graph signals Author Segarra, Santiago (University of Pennsylvania) Marques, Antonio G. (King Juan Carlos University) Leus, G.J.T. (TU Delft Signal Processing Systems) Ribeiro, Alejandro (University of Pennsylvania) Contributor Dong, Min (editor) Zheng, Thomas Fang (editor) Date 2016-05-19 Abstract A novel scheme for sampling graph signals is proposed. Space-shift sampling can be understood as a hybrid scheme that combines selection sampling -- observing the signal values on a subset of nodes - and aggregation sampling - observing the signal values at a single node after successive aggregation of local data. Under the assumption of bandlimitedness, we state conditions and propose strategies for signal recovery in different settings. Being a more general procedure, space-shift sampling achieves smaller reconstruction errors than current schemes, as we illustrate through the reconstruction of the industrial activity in a graph of the U.S. economy. Subject ReconstructionGraph signal processingSpace-shift samplingBandlimited signal To reference this document use: http://resolver.tudelft.nl/uuid:3853c34e-1ffb-4181-bedd-235a09957e1b DOI https://doi.org/10.1109/icassp.2016.7472900 Publisher IEEE, Danvers, MA ISBN 978-1-4799-9988-0 Source 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP): Proceedings Event 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016, 2016-03-20 → 2016-03-25, Shanghai International Convention Center, Shanghai, China Bibliographical note Accepted Author Manuscript Part of collection Institutional Repository Document type conference paper Rights © 2016 Santiago Segarra, Antonio G. Marques, G.J.T. Leus, Alejandro Ribeiro Files PDF 11035543_p.pdf 524.48 KB Close viewer /islandora/object/uuid:3853c34e-1ffb-4181-bedd-235a09957e1b/datastream/OBJ/view