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| A New Learning Algorithm Based on MCC for Colored Noise Interference Cancellation |
| Hua Qu, Wentao Ma, Jihong Zhao, Tao Wang |
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Abstract In view of the defect of adaptive filtering algorithm based on the
LMS in colored noise interference cancellation, we put forward a
kind of new adaptive iterative learning algorithm using correntropy
and Maximum Correntropy Criterion (MCC). The MCC and the gradient
descent algorithm are used to update the weights of filter. The
proposed algorithm can obtain an optimal factor of step length $\mu
(k)$ from the square error of angle to undertake an analysis, and in
order to illustrate the feasibility of the algorithm, the
convergence of the algorithm from the sequence of the convergence in
norm were analyzed. At the same time, a step-size control parameters
was introduced in the algorithm, according to the parameters set
constant values or variable values, the algorithm is defined as
NC-MCC (Normalized Constant-MCC) and NV-MCC (Normalized
Variable-MCC). The simulation results show that, in the signal
adding the colored noise, compared with NLMS algorithm, the proposed
algorithm is better and has good stability.
DOI: 10.12733/jics20101514
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