In this paper after analyzing the adaptation process of the proportionate normalized least mean
square (PNLMS) algorithm, a statistical model is obtained to describe the convergence process of each adaptive
filter coefficient. Inspired by this result, a modified PNLMS algorithm based on precise magnitude estimate is
proposed. The simulation results indicate that in contrast to the traditional PNLMS algorithm, the proposed
algorithm achieves faster convergence speed in the initial convergence state and lower misalignment in the stead
stage with much less computational complexity.
WEN Hao-xiang* (文昊翔), LAI Xiao-han (赖晓翰), CHEN Long-dao (陈隆道), CAI Zhong-fa (蔡忠法)
. An Improved Proportionate Normalized Least Mean Square Algorithm for Sparse Impulse Response Identification[J]. Journal of Shanghai Jiaotong University(Science), 2013
, 18(6)
: 742
-748
.
DOI: 10.1007/s12204-013-1460-8
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