Application of Wiener Filtering Techniques for Extraction of Evoked Potential

In the present study, the performances of two well-known linear filtering techniques are compared for extraction of auditory Evoked Potential (EP) from a relatively small number of sweeps. Both experimental and simulated data are filtered. Our filtering method consists of Wiener filtering (WF) applications, where conventional WF and Coherence Weighted WF (CWWF)) have been assessed in combination with the Subspace Method (SM). The application of the SM before filtering improves the performance of WF where the CWWF works better than the conventional WF in that case. In conclusion, most of the linear filters show definitely better performance compared to EA. WF effectively reduces the experimental time (to half of that required by EA). The SM that has recently been revealed in EP estimation is found to be a meaningful prefilter as it significantly reduces the noise level of raw data.