Diffusion least-mean P-power algorithms for distributed estimation in alpha-stable noise environments

A diffusion least-mean P-power (LMP) algorithm is proposed for distributed estimation in alpha-stable noise environments, which is one of the widely used models that appears in various environments. Compared with the diffusion least-mean squares algorithm, better performance is obtained for the diff...

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Bibliographic Details
Published in:Electronics letters Vol. 49; no. 21; pp. 1355 - 1356
Main Author: Wen, F
Format: Journal Article
Language:English
Published: Stevenage The Institution of Engineering and Technology 01.10.2013
Institution of Engineering and Technology
John Wiley & Sons, Inc
Subjects:
adaptive estimation
Algorithms
alpha‐stable distribution
alpha‐stable noise environment
Applied sciences
Detection, estimation, filtering, equalization, prediction
Diffusion
diffusion least‐mean P‐power algorithm
distributed estimation
Exact sciences and technology
impulse noise
Information, signal and communications theory
least mean squares methods
least‐mean square algorithm
LMP algorithm
Noise
Signal and communications theory
signal processing
Signal, noise
Telecommunications and information theory
Wireless communications
least mean squares methods
distributed estimation
signal processing
LMP algorithm
impulse noise
alpha-stable noise environment
least-mean square algorithm
alpha-stable distribution
adaptive estimation
diffusion least-mean P-power algorithm
Adaptive filter
Stable law
Least squares method
Modeling
ISSN:0013-5194, 1350-911X, 1350-911X
Online Access:Get full text
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Summary:A diffusion least-mean P-power (LMP) algorithm is proposed for distributed estimation in alpha-stable noise environments, which is one of the widely used models that appears in various environments. Compared with the diffusion least-mean squares algorithm, better performance is obtained for the diffusion LMP methods when the noise is with alpha-stable distribution.
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ISSN:0013-5194
1350-911X
1350-911X
DOI:10.1049/el.2013.2331