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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Veröffentlicht in:	2019 IEEE 2nd International Conference on Electronics and Communication Engineering (ICECE) S. 444 - 450
Hauptverfasser:	Shuhua, Lv, Zhi, Quan
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.12.2019
Schlagworte:	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-Zugang:	Volltext
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