International Journal of Advances in Electrical Engineering
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P-ISSN: 2708-4574, E-ISSN: 2708-4582

International Journal of Advances in Electrical Engineering


2025, Vol. 6, Issue 1, Part A
Generalized maximum correntropy criterion with spline adaptive filtering and b-spline basis functions for nonlinear system identification in noisy environments


Author(s): João Silva, Maria Fernandes, Pedro Oliveira and Ana Sousa

Abstract: Nonlinear system identification in noisy environments presents a significant challenge in adaptive filtering, particularly when dealing with impulsive noise, non-Gaussian distributions, and complex system dynamics. Traditional filtering approaches, including Least Mean Squares (LMS) and Recursive Least Squares (RLS), often exhibit performance degradation due to their reliance on second-order statistical assumptions. The Maximum Correntropy Criterion (MCC) has shown promise in improving robustness; however, it suffers from limitations in capturing highly nonlinear system behaviors. This study proposes a Generalized Maximum Correntropy Criterion (GMCC) with Spline Adaptive Filtering, leveraging B-spline basis functions to enhance function approximation and noise resilience. The GMCC framework was evaluated against LMS, RLS, and conventional MCC-based adaptive filtering methods across Gaussian, Laplacian, and impulsive noise environments. Experimental results demonstrate that GMCC consistently achieves lower Mean Squared Error (MSE) values across all noise scenarios, outperforming conventional approaches in both accuracy and convergence stability. Statistical analysis using ANOVA confirmed performance consistency, though differences were not statistically significant at the 95% confidence level. Practical applications include biomedical signal processing, financial modeling, radar tracking, and autonomous systems, where robust nonlinear filtering is essential. Future research should focus on optimizing computational efficiency, incorporating deep learning enhancements, and extending real-time implementations for IoT and edge computing applications.

DOI: 10.22271/27084574.2025.v6.i1a.81

Pages: 26-30 | Views: 99 | Downloads: 46

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International Journal of Advances in Electrical Engineering
How to cite this article:
João Silva, Maria Fernandes, Pedro Oliveira, Ana Sousa. Generalized maximum correntropy criterion with spline adaptive filtering and b-spline basis functions for nonlinear system identification in noisy environments. Int J Adv Electr Eng 2025;6(1):26-30. DOI: 10.22271/27084574.2025.v6.i1a.81
International Journal of Advances in Electrical Engineering
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