Unsupervised algorithms for distributed estimation over adaptive networks

Author

Bin Saeed, Muhammad O. ; Zerguine, Azzedine ; Zummo, S.A. ; Sayed, Ali H.

Author_Institution

Dept. of Electr. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, United Arab Emirates

fYear

2012

fDate

4-7 Nov. 2012

Firstpage

1780

Lastpage

1783

Abstract

This work shows how to develop distributed versions of block blind estimation techniques that have been proposed before for batch processing. Using diffusion adaptation techniques, data are accumulated at the nodes to form estimates of the auto-correlation matrices and to carry out local SVD and/or Cholesky decomposition steps. Local estimates at neighborhoods are then aggregated to provide online streaming estimates of the parameters of interest. Simulation results illustrate the performance of the algorithms.

Keywords

ad hoc networks; adaptive estimation; matrix algebra; singular value decomposition; Cholesky decomposition steps; ad-hoc network; adaptive networks; autocorrelation matrices; batch processing; block blind estimation techniques; diffusion adaptation techniques; distributed estimation; local SVD; online streaming; unsupervised algorithms; Blind estimation; Cholesky factorization; SVD; auto-correlation matrix; diffusion strategy;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers (ASILOMAR), 2012 Conference Record of the Forty Sixth Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

978-1-4673-5050-1

Type

conf

DOI

10.1109/ACSSC.2012.6489340

Filename

6489340