Open AccessThis article is
- freely available
Methods for Distributed Compressed Sensing
School of Electrical Engineering and ACCESS Linneaus Centre, KTH Royal Institute of Technology, Stockholm SE-100 44, Sweden
* Author to whom correspondence should be addressed.
Received: 15 October 2013; in revised form: 29 November 2013 / Accepted: 9 December 2013 / Published: 23 December 2013
Abstract: Compressed sensing is a thriving research field covering a class of problems where a large sparse signal is reconstructed from a few random measurements. In the presence of several sensor nodes measuring correlated sparse signals, improvements in terms of recovery quality or the requirement for a fewer number of local measurements can be expected if the nodes cooperate. In this paper, we provide an overview of the current literature regarding distributed compressed sensing; in particular, we discuss aspects of network topologies, signal models and recovery algorithms.
Keywords: distributed compressed sensing; distributed greedy pursuit; greedy algorithms
Article StatisticsClick here to load and display the download statistics.
Notes: Multiple requests from the same IP address are counted as one view.
Cite This Article
MDPI and ACS Style
Sundman, D.; Chatterjee, S.; Skoglund, M. Methods for Distributed Compressed Sensing. J. Sens. Actuator Netw. 2014, 3, 1-25.
Sundman D, Chatterjee S, Skoglund M. Methods for Distributed Compressed Sensing. Journal of Sensor and Actuator Networks. 2014; 3(1):1-25.
Sundman, Dennis; Chatterjee, Saikat; Skoglund, Mikael. 2014. "Methods for Distributed Compressed Sensing." J. Sens. Actuator Netw. 3, no. 1: 1-25.