时域和酉空间中基于最大相关熵准则的非线性噪声处理

针对非线性噪声处理的问题，考虑到信号的高阶统计量以及在酉空间可以很好地处理非高斯噪声，提出了在时域和酉空间中基于最大相关熵准则（MCC）的噪声处理算法。结合MCC和梯度下降算法，设计出了时域中非线性噪声的滤波算法。同时将该算法推广到酉空间中噪声处理，给出了酉空间中基于MCC的滤波算法。通过仿真研究发现,在时域和酉空间中，基于MCC的滤波算法相对于传统的基于最小均方差（LMS）的滤波算法在处理非高斯噪声的问题时有着显著优势，以更快的收敛速度达到能够较完整地保留信号特征的效果。

Max correntropy criteria-based nonlinear noise processing in time domain and unitary space

Considering the problems for nonlinear noise processing and taking account of that higher-order statistics of the signal and unitary space can be a good deal with non-Gaussian noise，the noise processing algorithm based on Max Correntropy Criteria (MCC) in the time domain and the unitary space was proposed. Combining the MCC and gradient descent algorithm, a nonlinear noise filtering algorithm in the time domain was designed. At the same time, extending the algorithm to the noise processing in the unitary space, the unitary space filtering algorithm based on the MCC was put forward. The simulation study shows that the algorithm based on the MCC algorithm has significant advantages compared with the traditional Least Mean Square (LMS) based filtering algorithm, which means it can achieve more complete signal characteristics by faster convergence.