To effectively suppress white noise and preserve more useful components of electrocardiogram(ECG) signal, a novel de-noising method based on morphological component analysis(MCA) is proposed. MCA is a method which all...To effectively suppress white noise and preserve more useful components of electrocardiogram(ECG) signal, a novel de-noising method based on morphological component analysis(MCA) is proposed. MCA is a method which allows us to separate features contained in an original signal when these features present different morphological aspects. According to the features of ECG, we used the UWT dictionary to sparsely represent mutated component, and used the DCT dictionary to sparsely represent smooth component. The experimental results of the samples choosing from MIT-BIH databases show that the MCA-based method is effective for white noise removal.展开更多
基金Natural Science Foundatoin of Fujian Province of Chinagrant number:2012J01280
文摘To effectively suppress white noise and preserve more useful components of electrocardiogram(ECG) signal, a novel de-noising method based on morphological component analysis(MCA) is proposed. MCA is a method which allows us to separate features contained in an original signal when these features present different morphological aspects. According to the features of ECG, we used the UWT dictionary to sparsely represent mutated component, and used the DCT dictionary to sparsely represent smooth component. The experimental results of the samples choosing from MIT-BIH databases show that the MCA-based method is effective for white noise removal.
