The LMS algorithm with delayed coefficient adaptation

The behavior of the delayed least-mean-square (DLMS) algorithm is studied. It is found that the step size in the coefficient update plays a key role in the convergence and stability of the algorithm. An upper bound for the step size is derived that ensures the stability of the DLMS. The relationship...

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Veröffentlicht in:	IEEE transactions on acoustics, speech, and signal processing speech, and signal processing, 1989-09, Vol.37 (9), p.1397-1405
Hauptverfasser:	Long, G., Ling, F., Proakis, J.G.
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Computer errors Convergence Delay Detection, estimation, filtering, equalization, prediction Equations Exact sciences and technology Filtering algorithms Information, signal and communications theory Least squares approximation Mean square error methods Signal and communications theory Signal processing algorithms Signal, noise Stability Telecommunications and information theory Upper bound
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Zusammenfassung:	The behavior of the delayed least-mean-square (DLMS) algorithm is studied. It is found that the step size in the coefficient update plays a key role in the convergence and stability of the algorithm. An upper bound for the step size is derived that ensures the stability of the DLMS. The relationship between the step size and the convergence speed, and the effect of the delay on the convergence speed, are also studied. The analytical results are supported by computer simulations.< >
ISSN:	0096-3518
DOI:	10.1109/29.31293