Automatic Regularization for Linear MMSE Filters

Author:

Daniel Gomes de Pinho Zanco, Leszek Szczecinski, Jacob Benesty

Keyword:

Computer Science, Information Theory, Information Theory (cs.IT), Machine Learning (cs.LG), Signal Processing (eess.SP)

journal:

date:

2023-12-11 00:00:00

Abstract

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.

PDF: Automatic Regularization for Linear MMSE Filters.pdf