Generalized Flexible Splitting Function Outperforms Classical Approaches in Blind Signal Separation of Complex Environment

This paper introduces a novel approach of blind separation in complex environment based on bi-dimensional flexible activation function (AF) and compares the performance of this architecture with the classical approach. The generalized complex function has been realized by a flexible bi-dimensional spline based approach both for the real and one for the imaginary parts, avoiding the restriction due to the Louiville's theorem. The flexibility of the surface allows the learning of the control points using a gradient-based techniques. Some experimental results demonstrate the effectiveness of the proposed method.