A Novel Method for Block Ambiguities of Independent Component Analysis using Previous Demixing Matrices

摘要

This manuscript deals with the permutation and scaling ambiguities inherent to an Independent Component Analysis (ICA) framework when continuously mixed signals are split in time and processed in a block-by-block manner. For each adjacent block, we choose the demixing matrix of the previous block as the initialization matrix for separating the subsequent block. By using the demixing matrices of the previous blocks, the separation process of the subsequent blocks is largely simplified, and the corresponding computational cost is thereby significantly reduced. Therefore, compared with previous similar methods, our proposed method is much more efficient in terms of computational speed, which is particularly striking when a large number of blocks is applied. We conducted simulations to validate the effectiveness of our proposed method.