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Wavelet Shrinkage Models for Denoising of Biomedical Signals: Wavelet based subband Shrinakge Models and their Applications in Denoising of Biomedical Signals - Softcover
In this thesis an efficient denoising models for biological signals using shrinkage function and shrikage based adaptive filters are addressed. Signal denoising, an important problem of signal processing aims to find an estimate of the original signal from the noisy signal. There exist various transform-domain algorithm based on performing orthogonal transformation, modifying transforms coefficients and inverse transforming the modified transform coefficients. In this thesis, transform- domain signal denoising algorithm are equipped with wavelet subband dependent threshold and prioritized shrinkage. Hence they are made more adaptive to the local variations of the signals, thus improving the overall denoising efficiency. The main objective of this work is to develop and implement a denoising model for reducing the noises present in biological signals such as ECE, EEG, PCG, Pulse, EMG etc., and to eliminate the power line frequency interference in these signals. The major work of this thesis is developement of three new shrinkage functions namely hyper, modified hyper and subband adaptive shrinkage.
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Dr. S. Poornachandra completed his UG in ECE from NIE, Mysore, PG in BME from MIT, Manipal and PhD in signal processing from Anna University, Chennai. He has published many research papers in leading journals and conferences and won best paper awards. He is a peer review committee member of journals. He has published many technical books.
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- PublisherLAP LAMBERT Academic Publishing
- Publication date2010
- ISBN 10 3838377087
- ISBN 13 9783838377087
- BindingPaperback
- Number of pages288
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Wavelet Shrinkage Models for Denoising of Biomedical Signals: Wavelet based subband Shrinakge Models and their Applications in Denoising of Biomedical Signals
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Wavelet Shrinkage Models for Denoising of Biomedical Signals
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Book Description Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this thesis an efficient denoising models for biological signals using shrinkage function and shrikage based adaptive filters are addressed. Signal denoising, an important problem of signal processing aims to find an estimate of the original signal from the noisy signal. There exist various transform-domain algorithm based on performing orthogonal transformation, modifying transforms coefficients and inverse transforming the modified transform coefficients. In this thesis, transform- domain signal denoising algorithm are equipped with wavelet subband dependent threshold and prioritized shrinkage. Hence they are made more adaptive to the local variations of the signals, thus improving the overall denoising efficiency. The main objective of this work is to develop and implement a denoising model for reducing the noises present in biological signals such as ECE, EEG, PCG, Pulse, EMG etc., and to eliminate the power line frequency interference in these signals. The major work of this thesis is developement of three new shrinkage functions namely hyper, modified hyper and subband adaptive shrinkage. 288 pp. Englisch. Seller Inventory # 9783838377087
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Wavelet Shrinkage Models for Denoising of Biomedical Signals Wavelet based subband Shrinakge Models and their Applications in Denoising of Biomedical Signals
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Book Description Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: S PoornachandraDr. S. Poornachandra completed his UG in ECE from NIE, Mysore, PG in BME from MIT, Manipal and PhD in signal processing from Anna University, Chennai. He has published many research papers in leading journals and co. Seller Inventory # 5417995
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Wavelet Shrinkage Models for Denoising of Biomedical Signals : Wavelet based subband Shrinakge Models and their Applications in Denoising of Biomedical Signals
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Book Description Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this thesis an efficient denoising models for biological signals using shrinkage function and shrikage based adaptive filters are addressed. Signal denoising, an important problem of signal processing aims to find an estimate of the original signal from the noisy signal. There exist various transform-domain algorithm based on performing orthogonal transformation, modifying transforms coefficients and inverse transforming the modified transform coefficients. In this thesis, transform- domain signal denoising algorithm are equipped with wavelet subband dependent threshold and prioritized shrinkage. Hence they are made more adaptive to the local variations of the signals, thus improving the overall denoising efficiency. The main objective of this work is to develop and implement a denoising model for reducing the noises present in biological signals such as ECE, EEG, PCG, Pulse, EMG etc., and to eliminate the power line frequency interference in these signals. The major work of this thesis is developement of three new shrinkage functions namely hyper, modified hyper and subband adaptive shrinkage. Seller Inventory # 9783838377087
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Wavelet Shrinkage Models for Denoising of Biomedical Signals Wavelet based subband Shrinakge Models and their Applications in Denoising of Biomedical Signals
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ISBN 13: 9783838377087
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