Adaptive Filtering Optimization Function (AFOF)

Version 2.0 (742 KB) by Daniela Martins

The AFOF was developed to help Matlab users to obtain the optimal adaptive filters and their parameters for a specific application.

https://github.com/danielamartins99/Adaptive-Filtering-Optimization-Function

0.0

(0)

42 Downloads

Updated 15 Oct 2022

View License on GitHub

Adaptive-Filtering-Optimization-Function

The AFOF was developed to help Matlab users to obtain the optimal adaptive filters and their parameters for a specific application. To run this function, Signal Processing and DSP System Toolboxes are necessary. See the AFOF_user_guide PDF for instructions.

Cite As

Daniela Martins (2026). Adaptive Filtering Optimization Function (AFOF) (https://github.com/danielamartins99/Adaptive-Filtering-Optimization-Function/releases/tag/2.0), GitHub. Retrieved January 18, 2026.

Martins, Daniela, et al. “Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram.” Sensors, vol. 22, no. 19, MDPI AG, Oct. 2022, p. 7638, doi:10.3390/s22197638.

View more styles

MATLAB Release Compatibility

Created with R2022a

Compatible with any release

Platform Compatibility

Windows macOS Linux

Tags Add Tags

Version	Published	Release Notes
2.0	15 Oct 2022	See release notes for this release on GitHub: https://github.com/danielamartins99/Adaptive-Filtering-Optimization-Function/releases/tag/2.0	Download

To view or report issues in this GitHub add-on, visit the GitHub Repository.

MLA	Martins, Daniela, et al. “Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram.” Sensors, vol. 22, no. 19, MDPI AG, Oct. 2022, p. 7638, doi:10.3390/s22197638.
APA	Martins, D., Batista, A., Mouriño, H., Russo, S., Esgalhado, F., Reis, C. R. P. dos, Serrano, F., et al. (2022). Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram. Sensors, 22(19), 7638. MDPI AG. Retrieved from https://doi.org/10.3390%2Fs22197638
BibTeX	@article{Martins_2022, doi = {10.3390/s22197638}, url = {https://doi.org/10.3390%2Fs22197638}, year = 2022, month = {oct}, publisher = {{MDPI} {AG}}, volume = {22}, number = {19}, pages = {7638}, author = {Daniela Martins and Arnaldo Batista and Helena Mouri{\~{n}}o and Sara Russo and Filipa Esgalhado and Catarina R. Palma dos Reis and F{\'{a}}tima Serrano and Manuel Ortigueira}, title = {Adaptive Filtering for the Maternal Respiration Signal Attenuation in the Uterine Electromyogram}, journal = {Sensors} }