Regular Section
An Improved Multivariate Wavelet Denoising Method Using Subspace Projection
2017 Volume E100.A Issue 3 Pages 769-775
Details
2017 Volume E100.A Issue 3 Pages 769-775
An improved multivariate wavelet denoising algorithm combined with subspace and principal component analysis is presented in this paper. The key element is deriving an optimal orthogonal matrix that can project the multivariate observation signal to a signal subspace from observation space. Univariate wavelet shrinkage operator is then applied to the projected signals channel-wise resulting in the improvement of the output SNR. Finally, principal component analysis is performed on the denoised signal in the observation space to further improve the denoising performance. Experimental results based on synthesized and real world ECG data verify the effectiveness of the proposed algorithm.
