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Type: Artigo de periódico
Title: A fast least-squares algorithm for linearly constrained adaptive filtering
Author: Resende, LS
Romano, JMT
Bellanger, MG
Abstract: An extension of the field of fast least-squares techniques is presented. It is shown that the adaptation gain, which is updated with a number of operations proportional to the number of transversal filter coefficients, can be used to update the coefficients of a linearly constrained adaptive filter. An algorithm that is robust to round-off errors is derived. It is general and flexible. It can handle multiple constraints and multichannel signals. Its performance is illustrated by simulations and compared with the classical LMS-based Frost algorithm.
Editor: Ieee-inst Electrical Electronics Engineers Inc
Rights: fechado
Identifier DOI: 10.1109/78.502329
Date Issue: 1996
Appears in Collections:Artigos e Materiais de Revistas Científicas - Unicamp

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