Compressed Sensing for Networked Data

By Jarvis D. Haupt, Waheed Uz Zaman Bajwa, Michael G. Rabbat, Robert D. Nowak. IEEE Signal Processing Magazine, 2008

555 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/77a5022598172d0b79b6e5e63ac26da7756e1f35

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Citations in the corpus

Compressed data aggregation for energy efficient wireless sensor networks (2011, methodology): “…technique appears to suggest a way of reducing the sensory data traffic for WSNs without the need for adapting to the data correlation structure [11], the complication involved in the interaction between data routing and CS-based aggregation has postponed the development on this front until…”
Gossip Algorithms for Distributed Signal Processing (2010, unknown): “illustrates, via numerical simulation, the tradeoff between varying kand the number of gossip iterations. For more on the theoretical performance guarantees achievable in this formulation, see [122], [123]. A gossip-based approach to solving the reconstruction problem in a distributed fashion is des”
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications (2014, background): “For more on the theoretical performance of decentralized compressive sensing, please refer to [142]–[144].”
An efficient algorithm for total variation regularization with applications to the single pixel camera and compressive sensing (2010, background): “Many applications have been studied, such as reconstruction or denoising of Magnetic Resonance Images (MRI) [29, 30], analog-to-information conversion [31], sensor networks [34, 35], and even homeland security [68].”
Exact Recoverability From Dense Corrupted Observations via $\ell _{1}$-Minimization (2011, background): “Finally, Section VIII summarizes this paper and makes some closing remarks.”
Compressive data gathering for large-scale wireless sensor networks (2009, background): “[17] also speculate the potential of using compressive sampling theory for data aggregation in a multi-hop WSN.”
Robust Lasso With Missing and Grossly Corrupted Observations (2011, methodology): “(17) It is worth noting that these two invertibility and mutual incoherence properties are exactly the same as the conditions used to establish the exact signed support recovery in the standard Lasso (e.g [16], [8], [5]).”