【摘要】 文章结合核函数,把基于信号稀疏特性的线性盲分离方法应用于非线性混叠情况而给出了一种非线性混叠信号盲分离算法。该算法首先将混叠信号映射到高维核特征空间,其次,在核特征空间中构造一组正交基,通过这组正交基将高维核特征空间的信号映射到这组正交基张成的参数空间中,从而把非线性混叠信号盲分离问题转化为参数空间的线性混叠信号盲分离问题。最后,在参数空间中,应用基于信号稀疏特性的线性盲分离方法对信号进行分离。该算法收敛精度较高,稳定性好。仿真结果表明该算法是有效的,具有良好的分离性能。更多还原

【Abstract】 In this paper,a nonlinear blind source separation algorithm is proposed by extending the linear blind source separation algorithm based on signal sparse property to the nonlinear domain.The received mixing signals are first mapped to high dimensional kernel feature space,and an orthonormal basis of the kernel feature space is constructed.Next,in the kernel feature space,the mixing signals are parameterized by the orthonormal basis.Finally,the linear blind source separation algorithm based on signal sparse property is applied to the parameterized mixing signals.The proposed algorithm is characterized by high accuracy and robustness.Simulation results illustrate the efficiency and the good performance of the algorithm.更多还原