MVSE (minimizes variance squared error) adaptive filtering subject to a constraint on MSE (mean squared error)
A new adaptive filtering algorithm which minimizes the variance of the squared error subject to a constraint on the mean squared error (MSE) is proposed and studied. For the adaptive linear combiner signal processing configuration, this algorithm, called the LVCMS algorithm for least variance subject to a constraint on mean squared error, has a gradient that is a weighted linear combination of the least mean square (LMS) and least mean fourth (LMF) algorithm gradients. Theoretical expressions are derived for the LVCMS algorithm convergence factor and misadjustment, and comparisons are made with the LMS and LMF adaptation rules for Gaussian, Laplacian, and uniform plant noise and driving term distributions. 12 refs., 1 fig.
- Research Organization:
- Sandia National Labs., Albuquerque, NM (USA); Texas A and M Univ., College Station (USA). Dept. of Electrical Engineering
- DOE Contract Number:
- AC04-76DP00789
- OSTI ID:
- 6624154
- Report Number(s):
- SAND-87-0823C; CONF-8703110-1; ON: DE87007859
- Country of Publication:
- United States
- Language:
- English
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