基于ICA-R的复值信号抽取方法

参考独立分量分析( independent component analysis with reference, ICA-R )通过引入参考信号而实现期望实值源信号的抽取,具有消除传统ICA输出顺序不确定性和显著降低运算量等优点.为此将ICA-R的优势拓展到期望复值源信号抽取.首先,将N维复值ICA问题转化为由其实部和虚部组成的2N维实值ICA问题;然后,利用期望源信号的实部参考信号或虚部参考信号进行ICA-R;最后,根据转换混合矩阵的结构特点,消除ICA-R抽取信号实部与虚部间的幅值不确定性,进而得到无附加相移的期望复值信号.计算机仿真和性能分析结果表明了所提方法的有效性.

Blind extraction of complex-valued signal using ICA-R

Independent component analysis with reference(ICA-R) extracts only desired signals by incorporating prior information as reference signals.It has several advantages,such as eliminating the ambiguity of traditional ICA and significantly reducing computational load.ICA-R is extended to extract a complex-valued signal of interest.First,an N-dimension complex ICA is transformed into a 2N-dimension real ICA formed by a real part and an imaginary part.Then,ICA-R is applied to the real part or the imaginary part t...