A New Variable Forgetting Factor-Based Bias-Compensated RLS Algorithm for Identification of FIR Systems With Input Noise and Its Hardware Implementation

This paper proposes a new variable forgetting factor QRD-based recursive least squares algorithm with bias compensation (VFF-QRRLS-BC) for system identification under input noise. A new variable forgetting factor scheme is proposed to improve its convergence speed and steady-state mean squares error...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE transactions on circuits and systems. I, Regular papers Vol. 67; no. 1; pp. 198 - 211
Main Authors:	Tan, Hai Jun, Chan, Shing Chow, Lin, Jian Qiang, Sun, Xu
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.01.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Additive noise Algorithms Bias bias compensation Compensation Computer simulation efficient hardware implementation Estimation Field programmable gate arrays Finite impulse response filters Finite impulse response model Hardware Impulse response Least squares method Linear arrays Lookup tables Noise Noise measurement Recursive methods Self calibration Steady state System identification variable forgetting factor
ISSN:	1549-8328, 1558-0806
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!