Performance of diffusion adaptation for collaborative optimization

Author

Chen, Jianshu ; Sayed, Ali H.

Author_Institution

Dept. of Electr. Eng., Univ. of California, Los Angeles, CA, USA

fYear

2012

fDate

25-30 March 2012

Firstpage

3753

Lastpage

3756

Abstract

We derive an adaptive diffusion mechanism to optimize global cost functions in a distributed manner over a network of nodes. The cost function is assumed to consist of the sum of individual components, and diffusion adaptation is used to enable the nodes to cooperate locally through in-network processing in order to solve the desired optimization problem. We analyze the mean-square-error performance of the algorithm, including its transient and steady-state behavior. We illustrate one application in the context of least-mean-squares estimation for sparse vectors.

Keywords

least mean squares methods; optimisation; sparse matrices; vectors; adaptive diffusion mechanism; collaborative optimization; diffusion adaptation performance; global cost function optimization; in-network processing; least mean squares estimation; mean square error performance; sparse vectors; steady-state behavior; transient behavior; Adaptive systems; Convergence; Cost function; Noise; Steady-state; Vectors; Distributed optimization; diffusion adaptation; energy conservation; in-network processing; learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on

Conference_Location

Kyoto

ISSN

1520-6149

Print_ISBN

978-1-4673-0045-2

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2012.6288733

Filename

6288733