Talks and Poster Presentations (with Proceedings-Entry):
V. Schwarz, G. Hannak, G. Matz:
"On the convergence of average consensus with generalized Metropolis-Hasting weights";
Talk: IEEE International Conference on Speech, Acoustics, and Signal Processing 2014 (ICASSP 2014),
Florence, Italy;
05-04-2014
- 05-09-2014; in: "Proc. IEEE ICASSP-2014",
IEEE,
(2014),
5442
- 5446.
English abstract:
Average consensus is a well-studied method for distributed averaging. The convergence properties of average consensus depend on the averaging weights. Examples for commonly used weight designs are Metropolis-Hastings (MH) weights and constant weights. In this paper, we provide a complete convergence analysis for a generalized MH weight design that encompasses conventional MH as special case. More specifically, we formulate sufficient and necessary conditions for convergence. A main conclusion is that AC with MH weights is guaranteed to converge unless the underlying network is a regular bipartite graph.
Keywords:
average consensus, wireless sensor networks, distributed algorithms
Electronic version of the publication:
http://publik.tuwien.ac.at/files/PubDat_227843.pdf
Created from the Publication Database of the Vienna University of Technology.