Blind Source Separation with Multi-Objective Optimization for Denoising

Blind Source Separation is an optimization method frequently used in statistical signal processing applications. There are many application areas such as ambient listening, denoising, detection, and so on. In this study, a new Strength Pareto Evolutionary Algorithm 2-based separation proposed, which combines Multi-Objective Optimization algorithms. The proposed has been tested for widely biomedical processing. That is, the Electrocardiogram (ECG) White Gaussian Noise mixed together with normally distributed random numbers original signals of obtained again. To evaluate performance others (Multi-Objective Independent Component Analysis), Signal-to-Noise Ratio (SNR) ECG from measured. As result simulation studies, it seen that satisfactory.