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Adaptive inverse filter

Conference ·
OSTI ID:10138664

This paper describes the design of an inverse adaptive filter, using the Least-Mean-Square (LMS) algorithm, the correct data taken with an analog filter. The gradient estimate used in the LMS algorithm is based upon the instantaneous error, e{sup 2}(n). Minimizing the mean-squared-error does not provide an optimal solution in this specific case. Therefore, another performance criterion, error power, was developed to calculate the optimal inverse model. Despite using a different performance criterion, the inverse filter converges rapidly and gives a small mean-squared-error. Computer simulations of this filter are also shown in this paper.

Research Organization:
Sandia National Labs., Albuquerque, NM (United States)
Sponsoring Organization:
USDOE, Washington, DC (United States)
DOE Contract Number:
AC04-76DP00789
OSTI ID:
10138664
Report Number(s):
SAND--92-0816C; CONF-9205141--1; ON: DE92011660
Country of Publication:
United States
Language:
English