Fractional tap-length algorithm for adaptive filters under maximum correntropy criterion

Accurate estimation of the optimum tap-length for the adaptive filter provides a good balance between the steady-state performance and the complexity of the adaptive algorithm. The convergence performance of the variable tap-length least mean square (LMS) adaptive filters under the minimum mean square error (MMSE) criterion deteriorates in the non-Gaussian noise environment. A fractional tap-length (FT) algorithm for the maximum correntropy criterion (MCC) adaptive filters, named FT-MCC algorithm, is proposed to solve the above problem. The proposed algorithm is based on the concept of the optimum tap-length for the MCC adaptive filters. The difference of the correntropy between adaptive filters with different tap-lengths is used to achieve the tap-length update. Both theoretical analysis and simulation result show that the proposed algorithm has strong robustness in non-Gaussian noise environment compared with other variable tap-length LMS algorithm and the optimum tap-length can be well estimated with proper parameter selection.