Novel Spectral Processing Methods in NMR Wavelet Transform and Pattern Based Analysis

dc.contributor.guideRamanathan, K V
dc.coverage.spatial
dc.creator.researcherAdilakshmi, Dwarasala
dc.date.accessioned2022-12-30T12:18:24Z
dc.date.available2022-12-30T12:18:24Z
dc.date.awarded2019
dc.date.completed2019
dc.date.registered
dc.description.abstractNMR spectroscopy provides a variety of information leading to an understanding of the properties of different materials. To extract this information from the experiments, one needs to have noise and artifacts free spectra and part of the present thesis examines ways of obtaining artifacts free spectra using wavelet transforms. The thesis addresses the inherent problem of low sensitivity of spin noise spectra and examines the utility of wavelet transform to mitigate this problem by distinguishing real peaks from the circuit-noise contaminated data. Suppression of the random circuit noise and the consequent enhancement of the correlated nuclear spin noise signal have been demonstrated with discrete wavelet transform. Spectra of both 1H and 13C nuclear spins have been considered and significant signal enhancements in both the cases have been observed. A detailed analysis of several possible wavelet, thresholding and decomposition solutions have been made to obtain the optimum conditions for signal enhancement. It is observed that the application of wavelet transform leaves the spin noise signal line shape essentially unchanged, which is an advantage for several applications involving spin noise spectra. Next, baseline distortions encountered in 1D NMR is considered and an algorithm is proposed for simultaneously denoising and base-line correction. Application of wavelet transform filters signals into high and low frequency components. The high frequency part contains mainly the signals of relevance as well as noise. Repeated application of wavelet transform leaves a low frequency component which has essentially the base-line information, that can be corrected in several ways. The high frequency component can also be subjected to noise-reduction algorithms. Combining these two parts back again in a reverse process, gives a spectrum that is essentially free of base-line distortions and with reduced noise. Another source of artifacts in modern NMR spectroscopy is the t1-noise. Though mitigated to a significant exten...
dc.description.note
dc.format.accompanyingmaterialNone
dc.format.dimensions30 cm.
dc.format.extentxv, 155p.
dc.identifier.urihttp://hdl.handle.net/10603/434396
dc.languageEnglish
dc.publisher.institutionPhysics
dc.publisher.placeBangalore
dc.publisher.universityIndian Institute of Science Bangalore
dc.relation
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordPhysical Sciences
dc.subject.keywordPhysics
dc.subject.keywordPhysics Multidisciplinary
dc.titleNovel Spectral Processing Methods in NMR Wavelet Transform and Pattern Based Analysis
dc.title.alternativeNovel Spectral Processing Methods in NMR Wavelet Transform and Pattern Based Analysis
dc.type.degreePh.D.

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