2019 Volume 13 Issue 2 Pages 95-107
Recent developments in computation and sensing technology have enabled us to access a variety of data sources. In signal processing and machine learning, sparse modeling has attracted much attention as a means of processing such high-dimensional data by harnessing the sparsity of a data structure. On the other hand, the importance of distributed sparse modeling over large-scale networks has also been increasing. In this paper, we discuss the theoretical background of the distributed sparse modeling from the viewpoint of cooperative control of multiagent systems. We also consider the application of distributed sparse modeling to environmental measurement with smart sensor networks.
