说明：  A Tensor-Based Method for Large-Scale Blind Source Separation Using Segmentation Many real-life signals are compressible, meaning that they depend on much fewer parameters than their sample size. In this paper, we use low-rank matrix or tensor representations for signal compression. We propose a new deterministic method for blind source separation that exploits the low-rank structure, en- abling a unique separation of