This paper proposes a novel method for blindly separating unobservable independent component (IC) signals based on the use of a genetic algorithm. It is intended for its applicati...
The technique of independent component analysis (ICA) is applied for texture feature detection. In ICA an optimal transformation (with respect to the statistical structure of the i...
The blind source separation (BSS) problem is often solved by maximizing objective functions reflecting the statistical independence between outputs. Since global maximization may...
In this paper, we propose to use the Huber M-estimator cost function as a contrast function within the complex FastICA algorithm of Bingham and Hyvarinen for the blind separation o...
A neural-based method for source separation in nonlinear mixture is proposed in this paper. A cost function, which consists of the mutual information and partial moments of the out...