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The Journal of the Acoustical Society of America
Article . 2019 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Direct adaptive equalization based on fast sparse recursive least squares algorithms for multiple-input multiple-output underwater acoustic communications

Authors: Zhen, Qin; Jun, Tao; Xiaoyan, Wang; Xinwei, Luo; Xiao, Han;

Direct adaptive equalization based on fast sparse recursive least squares algorithms for multiple-input multiple-output underwater acoustic communications

Abstract

The sparse direct adaptive equalizer (DAE) has recently attracted much attention in underwater acoustic (UWA) communications for its improved performance compared with conventional non-sparse DAEs. The recursive least squares (RLS) type sparse DAEs were barely studied, mainly due to their high complexity despite fast convergence. This letter presents several low-complexity sparse RLS algorithms for multiple-input multiple-output UWA channel equalization. The resulting fast sparse RLS DAEs are tested to be effective and outperform their non-sparse counterpart by experimental results.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Top 10%
Top 10%
hybrid