An Improved Strong Tracking Variable Forgetting Factor RLS Algorithm with Low Complexity for Dynamic System Identification

The recursive least squares (RLS) adaptive filter is an appealing choice in systems identification problems, mainly due to its fast convergence rate. However, it is computationally very complex, which may make it impractical for the identification of the large length impulse response, and the fixed...

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Bibliographic Details

Published in:	2019 IEEE 2nd International Conference on Electronics and Communication Engineering (ICECE) pp. 444 - 450
Main Authors:	Shuhua, Lv, Zhi, Quan
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.12.2019
Subjects:	Adaptive filters Complexity theory Convergence dichotomous coordinate descent Mathematical model recursive least squares Robustness strong tracking System identification Time-varying systems variable forgetting factor
Online Access:	Get full text
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