Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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The electrocardiogram ECG signal plays an important role in the primary diagnosis, prognosis and survival analysis of heart diseases. The ECG signal contains an important amount of information that can be exploited in different manners. However, during its acquisition it is often contaminated with different sources of noise making difficult its interpretation. In this paper, a new approach based on Morphological Top-Hat Transform (MTHT) is developed in order to suppress noises from the ECG signals. The morphological operators (dilation, erosion, opening, closing) constitute the fundamental stage of Top-Hat transform. Method presented in this paper is compared with the Visu Shrink, Sure Shrink, and Bayes Shrink methods. The experimental results indicated that the proposed methods in this work were better than the compared methods in terms of retaining the geometrical characteristics of the ECG signal, SNR. Due to its simplicity and its fast implementation, the method can easily be used in clinical medicine.
S.A.Taouli. 1970. \u201cECG Signal Denoising by Morphological Top-Hat Transform\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 13 (GJCST Volume 13 Issue C5): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
Total Score: 102
Country: Algeria
Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering
Authors: S.A.Taouli, F.Bereksi-Reguig (PhD/Dr. count: 0)
View Count (all-time): 316
Total Views (Real + Logic): 25612
Total Downloads (simulated): 10900
Publish Date: 1970 01, Thu
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The electrocardiogram ECG signal plays an important role in the primary diagnosis, prognosis and survival analysis of heart diseases. The ECG signal contains an important amount of information that can be exploited in different manners. However, during its acquisition it is often contaminated with different sources of noise making difficult its interpretation. In this paper, a new approach based on Morphological Top-Hat Transform (MTHT) is developed in order to suppress noises from the ECG signals. The morphological operators (dilation, erosion, opening, closing) constitute the fundamental stage of Top-Hat transform. Method presented in this paper is compared with the Visu Shrink, Sure Shrink, and Bayes Shrink methods. The experimental results indicated that the proposed methods in this work were better than the compared methods in terms of retaining the geometrical characteristics of the ECG signal, SNR. Due to its simplicity and its fast implementation, the method can easily be used in clinical medicine.
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