Induced Coherence Resonance in an Electrochemical System

Wednesday, 8 October 2014: 15:00
Expo Center, 1st Floor, Universal 6 (Moon Palace Resort)
R. Rico-Martínez (Instituto Tecnológico de Celaya), M. Calderón-Ramírez (Insituto Tecnológico de Celaya), E. Ramírez-Álvarez (Universidad Autonóma del Estado de Morelos), and P. Parmananda (Indian Institute of Technology Bombay)
Applying noise to an excitable electrochemical systems near homoclinic orbits may lead to the emergence of coherent dynamics. A noise driver-control was developed for this purpose, using a neural network reference model assisted by a Kalman filter. The model is constructed to predict the occurrence of spiking behavior and its long-term prediction describes the statistics of the spike train. The strategy involving the use of the Kalman filter allows for the on-line correction of model inaccuracies. This adaptive protocol is coupled with a stochastic search algorithm, allowing the pinpointing of the optimal noise amplitude that induces maximum coherence resonance in the system. The protocol was tested in an experimental Fe-potassium sulfate system, exhibiting a robust response even in the presence of electrochemical drift.