Absolute finite differences based variable forgetting factor RLS algorithm
Abstract Adaptive signal processing requires an efficient non‐stationarity detector. Most of the known non‐stationarity detection algorithms are based on residual statistics. The study proposes a novel non‐stationarity detection algorithm based on finite differences analysis of the processed signal....
Main Authors: | Slobodan Drašković, Željko Đurović, Vera Petrović |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi-IET
2022-02-01
|
Series: | IET Signal Processing |
Subjects: | |
Online Access: | https://doi.org/10.1049/sil2.12074 |
Similar Items
-
A Novel Method for Lithium-Ion Battery Online Parameter Identification Based on Variable Forgetting Factor Recursive Least Squares
by: Zizhou Lao, et al.
Published: (2018-05-01) -
Parameter Identification of DOC Model Based on Variable Forgetting Factor Least Squares
by: Hua Taoyi, et al.
Published: (2022-01-01) -
State of charge estimation of ultracapacitor based on forgetting factor recursive least square and extended Kalman filter algorithm at full temperature range
by: Jing Ren, et al.
Published: (2022-11-01) -
An Ultrafast Variable Forgetting Factor Recursive Least Square Method for Determining the State-of-Health of Li-Ion Batteries
by: Yuan Mao, et al.
Published: (2023-01-01) -
Adaptive Forgetting Factor Recursive Least Square Algorithm for Online Identification of Equivalent Circuit Model Parameters of a Lithium-Ion Battery
by: Xiangdong Sun, et al.
Published: (2019-06-01)