Noise Cancelation From ECG Signals Using Householder-RLS Adaptive Filter
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In this paper an adaptive recursive least squares filter is used for removal of artifacts from clinical ECG signals. The householder RLS (HRLS) algorithm is an efficient algorithm which recursively updates an arbitrary square-root of the input data correlation matrix and naturally provides the LS weight vector. A data dependent householder matrix is applied for such an update. In this paper an adaptive noise canceler (ANC) is designed for ECG denoising using HRLS algorithm. The promising characteristic of proposed ANC is its flexibility in choosing the reference signals, because it has a trade off between the correlation properties of the noise and the reference signals. Simulation results show the efficiency of RLS based algorithms in ECG denoising.
KeywordsElectrocardiography Adaptive filter Noise cancelation
The authors would like to acknowledge the financial support of Universiti Sains Malaysia for registration and attendance of the conference by short term grant.
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