Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/5529
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dc.contributor.authorChandel, Bhawna-
dc.contributor.authorSood, Meenakshi [Guided by]-
dc.date.accessioned2022-08-03T13:13:32Z-
dc.date.available2022-08-03T13:13:32Z-
dc.date.issued2017-
dc.identifier.urihttp://ir.juit.ac.in:8080/jspui//xmlui/handle/123456789/5529-
dc.description.abstractElectrocardiogram signal is noninvasive technique that has great importance in the detection of cardiac abnormalities. The analysis of ECG signal is preferred for conveying information as it preserves the electrical performance of heart. ECG signals are very sensitive and characteristics of ECG signals get contaminated due to different types of noise. In many of the biomedical applications, for real time heart monitoring system, it is necessary to remove the noise from ECG recordings to achieve faithful signals for further processing. In this thesis, various filters are used results to reduce and remove the effect of noise to get refined signal. The power spectral density and average power are performance metrics used before and after filtration. Adaptive filter is used for noise cancellation of ECG signal. Adaptive filter function is based on error minimization between input signal which is noisy ECG signal and its reference input. There are many adaptive algorithms such as Least Mean Square (LMS), Recursive Least Square (RLS), and Normalized Least Mean Square (NLMS) etc.en_US
dc.language.isoenen_US
dc.publisherJaypee University of Information Technology, Solan, H.P.en_US
dc.subjectElectrocardiogram signalen_US
dc.subjectECG signalsen_US
dc.subjectWavelet transformen_US
dc.subjectAlgorithmsen_US
dc.titleNoise Removal from ECG Signal Using Various Filtersen_US
dc.typeProject Reporten_US
Appears in Collections:Dissertations (M.Tech.)

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