HomeNewsListCongratulations on receiving GlobalSIP'15 Best Paper Award

Congratulations on receiving GlobalSIP'15 Best Paper Award

Congratulations to Xiaohan Wang, Jiaxuan Chen, and Yuantao Gu! The GlobalSIP'15 Best Paper Award Committee selected their paper titled "Generalized Graph Signal Sampling and Reconstruction" as Best Paper.


The IEEE Global Conference on Signal and Information Processing (GlobalSIP) is a flagship conference of the IEEE Signal Processing Society. GlobalSIP'15 is held in Orlando, Florida, USA, December 14-16, 2015. The conference will focus on signal and information processing with an emphasis on up-and-coming signal processing themes.


Generalized Graph Signal Sampling and Reconstruction


The emerging field of signal processing on graphs plays a more and more important role in processing signals and information related to networks. Existing works have shown that under certain conditions a smooth graph signal can be uniquely reconstructed from its decimation, i.e., data associated with a subset of vertices. However, in some potential applications (e.g., sensor networks with clustering structure), the obtained data may be a combination of signals associated with several vertices, rather than the decimation. In this paper, we propose a new concept of local measurement, which is a generalization of decimation. Using the local measurements, a local-set-based method named iterative local measurement reconstruction (ILMR) is proposed to reconstruct bandlimited graph signals. It is proved that ILMR can reconstruct the original signal perfectly under certain conditions. The performance of ILMR against noise is theoretically analyzed. The optimal choice of local weights and a greedy algorithm of local set partition are given in the sense of minimizing the expected reconstruction error. Compared with decimation, the proposed local measurement sampling and reconstruction scheme is more robust in noise existing scenarios.