Performance Enhancement of Adaptive Filters Using Preprocessing Technique by Wavelet Transform
In bio-medical signals, removal of noises is one of the major issues. In recent years, adaptive filtering plays an efficient role in processing and analysis of biomedical signals. An adaptive filter allows to detect time varying potentials and to track out the dynamic variations of the signals and it modify their behavior according to the input. This paper focuses on the enhancement of adaptive filters in biomedical field by preprocessing technique using wavelet transform. Preprocessing is a technique which process and remove the noises in the input before fed into the adaptive filters, which will further improves the performance of adaptive filters. At the end of this paper, a comparison study has been done between with and without preprocessing of adaptive filters based on Mean square error and Convergence rate. For that, we carried out the simulations on MIT-BIH database. The simulation results show that the performance of adaptive filters with preprocessing remove the noises much better than ordinary adaptive filters.