Comparison of neural algorithms for blind source separation in sensor array applications

A test bed of experiments with real and artificially generated data has been designed to compare the performance of three well-known algorithms for BSS. The main goal of these experiments was to extract some guidelines for their use in practical applications concerning their efficiency, accuracy, convergence speed, stability, and robustness under the presence of Gaussian noise and in presence of a large number of source signals.