Презентация Overcoming line broadening in real-time pure shift NMR spectroscopy онлайн
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- Тип файла:ppt / pptx (powerpoint)
- Всего слайдов:22 слайда
- Для класса:1,2,3,4,5,6,7,8,9,10,11
- Размер файла:695.08 kB
- Просмотров:59
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- Автор:неизвестен
Слайды и текст к этой презентации:
№1 слайд
Содержание слайда: Overcoming line broadening in real-time pure shift NMR spectroscopy
Alexandra Shchukina, Krzysztof Kazimierczuk
University of Warsaw, Centre of New Technologies, Poland
Craig Butts, Ikenna Ndukwe
Bristol University, UK
№2 слайд
Содержание слайда: Overcoming line broadening in real-time pure shift NMR spectroscopy
...with what?
Alexandra Shchukina, Krzysztof Kazimierczuk
University of Warsaw, Centre of New Technologies, Poland
Craig Butts, Ikenna Ndukwe
Bristol University, UK
№3 слайд
Содержание слайда: Overcoming line broadening in real-time pure shift NMR spectroscopy
...with CS reconstruction!
Alexandra Shchukina, Krzysztof Kazimierczuk
University of Warsaw, Centre of New Technologies, Poland
Craig Butts, Ikenna Ndukwe
Bristol University, UK
№4 слайд
Содержание слайда: Pure shift NMR: what for and how
Line broadening in real-time pure shift NMR
CS reconstruction as a remedy
Details of CS: the idea and its realization
Applications
№5 слайд
Содержание слайда: Pure shift NMR: what for and how
Line broadening in real-time pure shift NMR
CS reconstruction as a remedy
Details of CS: the idea and its realization
Applications
№6 слайд
Содержание слайда: Pure shift NMR as a tool for homodecoupling
№7 слайд
Содержание слайда: Selective pulses
Spacially selective
or
Frequency-selective
or
BIRD-based pulse sequences
...
№8 слайд
Содержание слайда: Pseudo-2D and real-time pure shift NMR
№9 слайд
Содержание слайда: Line broadening with concatenation
№10 слайд
Содержание слайда: Line broadening with concatenation
№11 слайд
Содержание слайда: Compressed Sensing – basic idea
A signal, which is sparse in some representation, can be undersampled (skip measurements) and then reconstructed mathematically
№12 слайд
Содержание слайда: Compressed Sensing – basic idea
A signal, which is sparse in some representation, can be undersampled (skip measurements) and then reconstructed mathematically
for NMR: spectrum
(Fourier transform of FID)
№13 слайд
Содержание слайда: Compressed Sensing – basic idea
A signal, which is sparse in some representation, can be undersampled (skip measurements) and then reconstructed mathematically
for NMR: spectrum
(Fourier transform of FID)
№14 слайд
Содержание слайда: Compressed Sensing – basic idea
A signal, which is sparse in some representation, can be undersampled (skip measurements) and then reconstructed mathematically
Full sampling: (full system),
– inverse Fourier transform, – spectrum, – FID
№15 слайд
Содержание слайда: Compressed Sensing – basic idea
A signal, which is sparse in some representation, can be undersampled (skip measurements) and then reconstructed mathematically
Full sampling: (full system),
– inverse Fourier transform, – spectrum, – FID
Undersampling: (undetermined system)
№16 слайд
Содержание слайда: Compressed Sensing – basic idea
A signal, which is sparse in some representation, can be undersampled (skip measurements) and then reconstructed mathematically
Full sampling: (full system),
– inverse Fourier transform, – spectrum, – FID
Undersampling: (undetermined system)
CS reconstruction: subject to
(out of all possible FIDs choose the one which gives the sparsest
spectrum)
№17 слайд
Содержание слайда: Compressed Sensing – basic idea
A signal, which is sparse in some representation, can be undersampled (skip measurements) and then reconstructed mathematically
Full sampling: (full system),
– inverse Fourier transform, – spectrum, – FID
Undersampling: (undetermined system)
CS reconstruction: subject to
(out of all possible FIDs choose the one which gives the sparsest
spectrum)
Taking noise into account:
№18 слайд
Содержание слайда: Compressed Sensing – basic idea
A signal, which is sparse in some representation, can be undersampled (skip measurements) and then reconstructed mathematically
Full sampling: (full system),
– inverse Fourier transform, – spectrum, – FID
Undersampling: (undetermined system)
CS reconstruction: subject to
(out of all possible FIDs choose the one which gives the sparsest
spectrum)
Taking noise into account:
№19 слайд
Содержание слайда: Compressed Sensing – basic idea
A signal, which is sparse in some representation, can be undersampled (skip measurements) and then reconstructed mathematically
Full sampling: (full system),
– inverse Fourier transform, – spectrum, – FID
Undersampling: (undetermined system)
CS reconstruction: subject to
(out of all possible FIDs choose the one which gives the sparsest
spectrum)
Taking noise into account:
Iterative solution → family of algorithms
№20 слайд
Содержание слайда:
№21 слайд
Содержание слайда:
№22 слайд
Содержание слайда:
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