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Adaptive filtering algorithms designed using control Liapunov functions
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DOI：10.1109/LSP.2005.863659.png)
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摘要
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The standard conjugate gradient (CG) method uses orthogonality of the residues to simplify the formulas for the parameters necessary for convergence. In adaptive filtering, the sample-by-sample update of the correlation matrix and the cross-correlation vector causes a loss of the residue orthogonality in a modified online algorithm, which, in turn, results in loss of convergence and an increase of the filter quadratic mean error. This letter extends a recently proposed control Liapunov function analysis of the CG method viewed as a dynamic system in the standard feedback configuration to the case of adaptive filtering.
Keyword:
adaptive equalizer
adaptive filtering algorithms
control Liapunov function (CLF)
iterative methods
linear prediction
system identification
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期刊
IF:
9.6
论文数:
1.1W
被引数:
1.7W
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