This paper is to present a high order statistics-based adaptive interference cancel filter (AIC-HOS) to process evoked potential (EP). In conventional ensemble averaging method, experiments have to conduct repetitively to record the required data. In normalized LMS adaptive filter, inappropriate step size always causes deficiency. This AIC-HOS system has none of the above disadvantages. This system was experimented in somatosensory evoked potential corrupted with EEG. Gradient type algorithm is used in this AIC-HOS structure to regulate the SNR of EEG and EP. This method is also simulated with visual evoked potential and audio evoked potential. The results obtained are satisfactory and acceptable in clinical usage. The AIC-HOS is superior to normalized LMS using adaptive filter in that it converges easily. Moreover, it is not sensitive to selection of step size in stabilities in convergency.
|頁（從 - 到）||2094-2096|
|期刊||Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings|
|出版狀態||Published - 1 12月 2001|
|事件||23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Istanbul, Turkey|
持續時間: 25 10月 2001 → 28 10月 2001