A novel blind source separation method based on monotonic functions and its application to ion-selective electrode arrays

Signal processing methods based on blind source separation (BSS) have been successfully applied to deal with the interference problem in ion-selective electrode (ISE) arrays. So far, the development of BSS methods to ISE arrays strongly relied on the Nicolsky-Eisenman (NE) model. Since this model provides a rough approximation in certain situations, the present paper aims at improving the existing BSS solutions by refining the mixing model based on the NE equation. More precisely, we place a set of polynomial monotonic functions after the standard logarithmic functions within the NE. The obtained results are preliminary but attest that the proposal lead to slight improvements and open the way for investigations on alternative monotonic compensating functions.