TY - GEN

T1 - Sample convergence of the normed LMS algorithm with feedback delay

AU - Voltz, Peter J.

PY - 1991

Y1 - 1991

N2 - When a delay of even one iteration is introduced in the coefficient update loop, the projection properties of the NLMS (normed least mean square) algorithm are lost, allowing the error vector to increase as well as decrease in any given update. This makes the analysis of the algorithm with delay much more difficult. An exact analysis of the delayed update algorithm, on a sample function basis, is developed. It is shown that for any delay, the gain parameter, can be chosen sufficiently small to guarantee exponential convergence, assuming only that the input satisfies the standard mixing condition.

AB - When a delay of even one iteration is introduced in the coefficient update loop, the projection properties of the NLMS (normed least mean square) algorithm are lost, allowing the error vector to increase as well as decrease in any given update. This makes the analysis of the algorithm with delay much more difficult. An exact analysis of the delayed update algorithm, on a sample function basis, is developed. It is shown that for any delay, the gain parameter, can be chosen sufficiently small to guarantee exponential convergence, assuming only that the input satisfies the standard mixing condition.

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M3 - Conference contribution

AN - SCOPUS:0026287622

SN - 078030033

T3 - Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing

SP - 2129

EP - 2132

BT - Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing

PB - Publ by IEEE

T2 - Proceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing - ICASSP 91

Y2 - 14 May 1991 through 17 May 1991

ER -