Exponential Inverse Square Root Recursive Spline Adaptive Filter for Nonlinear System Identification.
Saved in:
| Title: | Exponential Inverse Square Root Recursive Spline Adaptive Filter for Nonlinear System Identification. |
|---|---|
| Authors: | Chikyal, Neetu1,2 (AUTHOR) cn720055@student.nitw.ac.in, Vasundhara1 (AUTHOR) vasundhara@nitw.ac.in, Bhar, Chayan1 (AUTHOR) cbhar@nitw.ac.in |
| Source: | Circuits, Systems & Signal Processing. Sep2025, Vol. 44 Issue 9, p6352-6373. 22p. |
| Subjects: | Adaptive filters, Nonlinear estimation, Robust control, Random noise theory, Computer simulation |
| Abstract: | Lately, an adaptive exponential functional link network and its variants have been employed for nonlinear system identification. The nonlinear filters constructed upon spline exhibit efficacious nonlinear modelling along with lesser computations. However, non-Gaussian interference deteriorates the modelling ability of such nonlinear filters. Therefore, instead of this, the present manuscript intends to present a new exponential inverse square root recursive spline adaptive filter (EISSAF) for nonlinear system modelling. It incorporates a newly proposed exponential inverse square root cost criteria for imparting robustness to the proposed algorithm in the wake of non-Gaussian or impulsive noise contamination. The weight adaptation rule has been derived for the proposed method. Varied numerical simulations assert the potency of the introduced spline-dependent methodology in nonlinear system identification. [ABSTRACT FROM AUTHOR] |
| Copyright of Circuits, Systems & Signal Processing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | Lately, an adaptive exponential functional link network and its variants have been employed for nonlinear system identification. The nonlinear filters constructed upon spline exhibit efficacious nonlinear modelling along with lesser computations. However, non-Gaussian interference deteriorates the modelling ability of such nonlinear filters. Therefore, instead of this, the present manuscript intends to present a new exponential inverse square root recursive spline adaptive filter (EISSAF) for nonlinear system modelling. It incorporates a newly proposed exponential inverse square root cost criteria for imparting robustness to the proposed algorithm in the wake of non-Gaussian or impulsive noise contamination. The weight adaptation rule has been derived for the proposed method. Varied numerical simulations assert the potency of the introduced spline-dependent methodology in nonlinear system identification. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 0278081X |
| DOI: | 10.1007/s00034-025-03076-y |
