Regularization plays a fundamental role in adaptive filtering. There are, very likely, many different ways to regularize an adaptive filter. In this letter, we propose one possible way to do it based on a condition that makes intuitively sense. From this condition, we show how to regularize the recursive least-squares (RLS) algorithm.
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Jacob BENESTY, Constantin PALEOLOGU, Silviu CIOCHIN, "Regularization of the RLS Algorithm" in IEICE TRANSACTIONS on Fundamentals,
vol. E94-A, no. 8, pp. 1628-1629, August 2011, doi: 10.1587/transfun.E94.A.1628.
Abstract: Regularization plays a fundamental role in adaptive filtering. There are, very likely, many different ways to regularize an adaptive filter. In this letter, we propose one possible way to do it based on a condition that makes intuitively sense. From this condition, we show how to regularize the recursive least-squares (RLS) algorithm.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E94.A.1628/_p
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@ARTICLE{e94-a_8_1628,
author={Jacob BENESTY, Constantin PALEOLOGU, Silviu CIOCHIN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Regularization of the RLS Algorithm},
year={2011},
volume={E94-A},
number={8},
pages={1628-1629},
abstract={Regularization plays a fundamental role in adaptive filtering. There are, very likely, many different ways to regularize an adaptive filter. In this letter, we propose one possible way to do it based on a condition that makes intuitively sense. From this condition, we show how to regularize the recursive least-squares (RLS) algorithm.},
keywords={},
doi={10.1587/transfun.E94.A.1628},
ISSN={1745-1337},
month={August},}
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TY - JOUR
TI - Regularization of the RLS Algorithm
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1628
EP - 1629
AU - Jacob BENESTY
AU - Constantin PALEOLOGU
AU - Silviu CIOCHIN
PY - 2011
DO - 10.1587/transfun.E94.A.1628
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E94-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2011
AB - Regularization plays a fundamental role in adaptive filtering. There are, very likely, many different ways to regularize an adaptive filter. In this letter, we propose one possible way to do it based on a condition that makes intuitively sense. From this condition, we show how to regularize the recursive least-squares (RLS) algorithm.
ER -