Paper Info
Title
Serial-inspired diffusion based on message passing for distributed estimation in adaptive networks
Abstract
Distributed estimation and processing in networks modeled by graphs have received a great deal of interest recently, due to the benefits of decentralised processing in terms of performance and robustness to communications link failure between nodes of the network. Diffusion-based algorithms have been demonstrated to be among the most effective for distributed signal processing problems, through the combination of local node estimate updates and sharing of information with neighbour nodes through diffusion. In this work, we develop a serial-inspired approach based on message-passing strategies that provides a significant improvement in performance over prior art. The concept of serial processing in the graph has been successfully applied in sum-product based algorithms and here provides inspiration for an algorithm which makes use of the most up-to-date information in the graph in combination with the diffusion approach to offer improved performance.
Year
DOI
Venue
2016
10.1109/SAM.2016.7569677
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)
Keywords
Field
DocType
Diffusion networks,wireless sensor networks,distributed processing
Convergence (routing),Signal processing,Graph,Serial memory processing,Computer science,Robustness (computer science),Schedule,Message passing,Signal processing algorithms,Distributed computing
Conference
ISBN
Citations 
PageRank 
978-1-5090-2104-8
0
0.34
References 
Authors
21
2
Name
Order
Citations
PageRank
Cornelius T. Healy1948.96
Rodrigo C. de Lamare21461179.59