Matrix computations (3rd ed.)
Adaptive blind separation with an unknown number of sources
Neural Computation
Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
| Hi-index | 0.00 |
This manuscript deals with the blind source separation problem with an instantaneous but dynamical mixture model. This study is limited to the case when the number of sources is time-variant. Theoretically, when new sources are detected, a new separating matrix should be estimated in order to extract all sources. However this effort implies an overwhelm computational cost. Our idea consists to use the previous separating matrix which was estimated before the appearance of the new sources. Owing to this point, the computational time and cost can be effectively reduced compared with the conventional separation scheme. Our new algorithm was corroborated with many simulations. Some results are given in the manuscript. The obtained and presented results clearly show that the proposed method outperformed the conventional method in processing time as well as in separation quality.