Paper Info
Title
A new LMS strategy for sparse estimation in adaptive networks.
Abstract
Recently several algorithms have been developed to exploit the distributive nature of an ad hoc wireless sensor network to estimate a certain parameter of interest. However, no work has been done to specifically address the issue of estimation of a sparse parameter. Recently, a sparse estimation algorithm based on the LMS algorithm was proposed. This work proposes a new sparse LMS algorithm for parameter estimation in adaptive networks. Two different schemes are used for incorporating the sparse LMS algorithm into the adaptive network framework. Simulation results show that in a sparse environment the proposed algorithms perform better than the LMS algorithm.
Year
DOI
Venue
2012
10.1109/PIMRC.2012.6362628
PIMRC
Keywords
Field
DocType
ad hoc networks,least mean squares methods,wireless sensor networks,LMS strategy,ad hoc wireless sensor network,adaptive network framework,distributive nature,parameter estimation,sparse estimation,Adaptive filters,diffusion algorithm,distributed networks,incremental algorithm,least mean square algorithm,sparse estimation
Computer science,Real-time computing,Artificial intelligence,Adaptive filter,Wireless ad hoc network,Estimation theory,Least mean squares filter,Algorithm design,Adaptive system,Sparse approximation,Algorithm,Wireless sensor network,Machine learning
Conference
Citations 
PageRank 
References 
2
0.36
6
Authors
2
Name
Order
Citations
PageRank
Muhammad Omer Bin Saeed1435.98
Asrar U. H. Sheikh222434.41