Adaptive equalisation in oversampled subbands

S. Weiß; S. R. Dooley; R. W. Stewart; A. K. Nandi

doi:10.1049/el:19981085

Adaptive equalisation in oversampled subbands

S. Weiß, S. R. Dooley, R. W. Stewart, A. K. Nandi

Electronic And Electrical Engineering

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25 Citations (Scopus)

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Abstract

The potential presence of fractional delays, nonminimum phase parts, and a colouring of the channel output can require adaptive equalisers to adapt very long filters, which can have slow convergence for LMS-type adaptive algorithms. The authors present a novel oversampled subband approach to adaptive equalisation, which can both significantly reduce computational complexity and improve convergence speed.

Original language	English
Pages (from-to)	1452-1453
Number of pages	2
Journal	Electronics Letters
Volume	34
Issue number	15
DOIs	https://doi.org/10.1049/el:19981085
Publication status	Published - 23 Jul 1998

Keywords

adaptive equalisers
adaptive filters
computational complexity
filtering theory

Access to Document

10.1049/el:19981085

Weiss98hAccepted author manuscript, 176 KB

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title = "Adaptive equalisation in oversampled subbands",

abstract = "The potential presence of fractional delays, nonminimum phase parts, and a colouring of the channel output can require adaptive equalisers to adapt very long filters, which can have slow convergence for LMS-type adaptive algorithms. The authors present a novel oversampled subband approach to adaptive equalisation, which can both significantly reduce computational complexity and improve convergence speed.",

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AU - Stewart, R. W.

AU - Nandi, A. K.

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AB - The potential presence of fractional delays, nonminimum phase parts, and a colouring of the channel output can require adaptive equalisers to adapt very long filters, which can have slow convergence for LMS-type adaptive algorithms. The authors present a novel oversampled subband approach to adaptive equalisation, which can both significantly reduce computational complexity and improve convergence speed.

KW - adaptive equalisers

KW - adaptive filters

KW - computational complexity

KW - filtering theory

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