Automatic Regularization for Linear MMSE Filters
CoRR(2023)
摘要
In this work, we consider the problem of regularization in minimum
mean-squared error (MMSE) linear filters. Exploiting the relationship with
statistical machine learning methods, the regularization parameter is found
from the observed signals in a simple and automatic manner. The proposed
approach is illustrated through system identification examples, where the
automatic regularization yields near-optimal results.
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