A smart universal single-channel blind source separation method and applications

In industrial, biological, medical and many more scenarios, single-channel blind source separation still remains challenges. A smart universal single-channel blind source separation method, the iterative heuristic general hybrid model with evaluation parameters feedback, Loop-BAS-VMD-ICA, is proposed and verified to recover the original sources automatically in multiple scenarios. Combined with beetle antennae search algorithm based variational mode decomposition and independent component analysis, by designing a new fitness function armed with processing effects of variational mode decomposition components and the final candidate source signals in each step of beetle antennae search algorithm, this model allows us to reconstruct a new optimized vector combining the selected components of variational mode decomposition with the original observation signal through a new scheme by loop mode with evaluation parameters feedback, and then the new vector is used to separate and extract independent source signals by iterative and heuristic calculation. Experimental results show that our method is not only smart, good versatile but also outperforms the state-of-the-art traditional time–frequency-based methods in extraction accuracy and waveform integrity. Compared with the state-of-the-art deep learning based methods, our method also demonstrates its unique advantages. It provides a better and more extensive means for the analysis and application of multicomponent signals.