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- W2187616226 abstract "Average consensus algorithms have attracted popularity in the wire less sensor network scenario as a simple way to compute linear com binations of the observations gathered by the sensors, in a totally de centralized fashion, Le., without a fusion center. However, average consensus techniques involve the iterated exchange of data among sensors. In a practical implementation, this interaction is affected by noise. The goal of this paper is to bring some common adap tive signal processing techniques into the sensor network context in order to robustify the iterative exchange of data against communica tion noise. In particular, we will compare the performance of two algorithms: a) a method, reminiscent of stochastic approximation algorithms, using a decreasing step size, with proper decaying law, and b) a leakage method imposing that the consensus cannot be too distant from the initial measurements. We provide a theoretical anal ysis, validated by simulation results, of both methods to show how to derive the best tradeoff between the system parameters in order to get the minimum estimation variance, taking into account both observation and interaction noise." @default.
- W2187616226 created "2016-06-24" @default.
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- W2187616226 date "2008-01-01" @default.
- W2187616226 modified "2023-09-27" @default.
- W2187616226 title "AVERAGE CONSENSUS ALGORITHMSROBUST AGAINST CHANNELNOISE" @default.
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