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Convergence properties of an adaptive digital lattice filter

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2 Author(s)
Honig, M. ; University of California, Berkeley, California ; Messerschmitt, D.G.

Convergence properties of a continuously adaptive digital lattice filter used as a linear predictor are investigated for both an unnormalized and a normalized gradient adaptation algorithm. The PARCOR coefficient mean value and the output mean square error are approximated and a simple model is described which approximates these quantities as functions of time. Calculated curves using this model are compared with simulation results. Results obtained for a two stage lattice are then compared with the two-stage 1ms transversal filter algorithm, demonstrating that it is possible but unlikely for the transversal filter to converge faster than the analogous lattice filter.

Published in:

Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '80.  (Volume:5 )

Date of Conference:

Apr 1980

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