Convex Combination of Adaptive Filters under the Maximum Correntropy Criterion in Impulsive Interference

• Published in: IEEE signal processing letters Vol. 21; no. 11; pp. 1385 - 1388
• Main Authors: Shi, Liming, Lin, Yun
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive algorithms; Adaptive filtering; Adaptive filters; Algorithms; Convergence; convex combination; Criteria; Errors; impulsive interference; Interference; maximum correntropy criterion; Mean square error methods; Mean square errors; Mean square values; Robustness; Signal processing algorithms; Steady-state; Tracking; weight transfer
• ISSN: 1070-9908; 1558-2361
• DOI: 10.1109/LSP.2014.2337899

A robust adaptive filtering algorithm based on the convex combination of two adaptive filters under the maximum correntropy criterion (MCC) is proposed. Compared with conventional minimum mean square error (MSE) criterion-based adaptive filtering algorithm, the MCC-based algorithm shows a better robustness against impulsive interference. However, its major drawback is the conflicting requirements between convergence speed and steady-state mean square error. In this letter, we use the convex combination method to overcome the tradeoff problem. Instead of minimizing the squared error to update the mixing parameter in conventional convex combination scheme, the method of maximizing the correntropy is introduced to make the proposed algorithm more robust against impulsive interference. Additionally, we report a novel weight transfer method to further improve the tracking performance. The good performance in terms of convergence rate and steady-state mean square error is demonstrated in plant identification scenarios that include impulsive interference and abrupt changes.