Using an Evolutionary Denoising Approach to Improve the Robustness of Chaotic Synchronization*

Chaotic synchronization in master-slave networks has been extensively studied in the last years, with a relevant impact in application domains like communication systems and the modeling of neuronal and other biomedical signals and systems. Many recent papers have shown that chaotic synchronization is easily lost when there is additive noise in the link between master and slave. This lack of robustness can simply derail the use of chaos-based communication systems in non-ideal environments. In the present work we employ a bio-inspired optimization technique to increase the signal-to-noise-ratio of the chaotic signal that arrives in the slave node of a master-slave discrete-time network and we show that this technique can improve the robustness of the chaotic synchronization to noise.