一种消除误差累积的多级快速独立分量分析算法

针对传统串行FastICA算法存在误差累积的缺点，该文提出一个多级结构的快速独立分量分析算法(MSFICA)。该算法采用两级结构来消除误差累积。为了降低算法的计算复杂度，第1级采用一种维数不断降低的方法来得到分离向量的初始值。第2级利用第1级得到的初始值直接对白化后的观测信号进行处理，不需要进行正交投影。仿真结果表明，该文提出的算法在增加少量计算复杂度的情况下，成功消除了误差累积，并且比已有的消除误差累积的并行算法有更好的SINR性能和BER性能。

A Multi-stage FastICA Algorithm to Remove Error Propagation

This paper proposes a Multi-Stage FastICA Algorithm(MSFICA) to solve the problem of error propagation in the traditional successive FastICA algorithm. MSFICA removes the error propagation effect through a two-stage structure. In order to reduce the computational complexity, a dimension decrease method is used to get the initial values of separating vectors in the first stage. In the second stage, the algorithm uses the initial values and whitened observed signals to separate original signals, and does not need orthogonal projection. Simulation results indicate that the proposed algorithm can eliminate error propagation successfully and achieve better performance than existing parallel FastICA algorithm at the expense of a slightly increased complexity.