This paper describes subband dependent adaptive shrinkage function that generalizes hard and soft shrinkages proposed by Donoho and Johnstone (1994). The proposed new class of shrinkage function has continuous derivative, which has been simulated and tested with normal and abnormal ECG signals with added standard Gaussian noise using MATLAB. The recovered signal is visually pleasant compared with other existing shrinkage functions. The implication of the proposed shrinkage function in denoising and data compression is discussed.
References
-
DL Donoho, De-noising by soft thresholding. IEEE Transactions on Information Theory 41(3), 613–627 (1995). Publisher Full Text
-
H-Y Gao, Wavelet shrinkage denoising using the non-negative garrote. Journal of Computational and Graphical Statistics 7(4), 469–488 (1998). Publisher Full Text
-
GA Bruce, H-Y Gao, Understanding WaveShrink: variance and bias estimation. Biometrika 83(4), 727–745 (1996). Publisher Full Text
-
X-P Zhang, MD Desai, Adaptive denoising based on SURE risk. IEEE Signal Processing Letters 5(10), 265–267 (1998). Publisher Full Text
-
C Stein, Estimation of the mean of a multivariate normal distribution. Annals of Statistics 9(6), 1135–1151 (1981). Publisher Full Text
-
H-Y Gao, AG Bruce, Waveshrink with firm shrinkage. Statistica Sinica 7(4), 855–874 (1997)
-
S Poornachandra, N Kumaravel, Hyper-trim shrinkage for denoising of ECG signal. Digital Signal Processing 15(3), 317–327 (2005)