DSpace
 
  Repositório Institucional da Universidade de Aveiro > Departamento de Electrónica, Telecomunicações e Informática > DETI - Artigos >
 Separation of water artifacts in 2D NOESY protein spectra using congruent matrix pencils
Please use this identifier to cite or link to this item http://hdl.handle.net/10773/5822

title: Separation of water artifacts in 2D NOESY protein spectra using congruent matrix pencils
authors: Stadlthanner, K.
Tomé, A. M.
Theis, F. J.
Gronwald, W.
Kalbitzer, H. R.
Lang, E. W.
keywords: Blind source separation
Independent component analysis
Generalized eigenvalue decomposition
Matrix pencil
2D NOESY Proton NMR spectra
issue date: Jan-2006
publisher: Elsevier
abstract: Multidimensional proton nuclear magnetic resonance spectra of biomolecules dissolved in aqueous solutions are usually contaminated by an intense water artifact. We discuss the application of a generalized eigenvalue decomposition (GEVD) method using a matrix pencil to solve the blind source separation (BSS) problem of removing the intense solvent peak and related artifacts. The method explores correlation matrices of the signals and their filtered versions in the frequency domain and implements a two-step algebraic procedure to solve the GEVD. Two-dimensional nuclear Overhauser enhancement spectroscopy (2D NOESY) of dissolved proteins is studied. Results are compared to those obtained with the SOBI [Belouchrani et al., IEEE Trans. Signal Process. 45(2) (1997) 434–444] algorithm which jointly diagonalizes several time-delayed correlation matrices and to those of the fastICA [Hyvärinen and Oja, Neural Comput. 9 (1996) 1483–1492] algorithm which exploits higher order statistical dependencies of random variables.
URI: http://hdl.handle.net/10773/5822
ISSN: 0925-2312
publisher version/DOI: http://dx.doi.org/10.1016/j.neucom.2005.02.008
source: Neurocomputing
appears in collectionsDETI - Artigos

files in this item

file description sizeformat
sdarticleNMRjna2006.pdf575.7 kBAdobe PDFview/open
Restrict Access. You can Request a copy!
statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! RCAAP OpenAIRE DeGóis
ria-repositorio@ua.pt - Copyright ©   Universidade de Aveiro - RIA Statistics - Powered by MIT's DSpace software, Version 1.6.2