Title :
A high-resolution technique for multidimensional NMR spectroscopy
Author :
Li, Ye ; Razavilar, Javad ; Liu, K. J Ray
Author_Institution :
AT&T Labs.-Res., Red Bank, NJ, USA
Abstract :
A scheme for estimating frequencies and damping factors of multidimensional nuclear magnetic resonance (NMR) data is presented-multidimensional NMR data can be modeled as the sum of several multidimensional damped sinusoids. The estimated frequencies and damping factors of multidimensional NMR data play important roles in determining protein structures. The authors present a high-resolution subspace method for estimating the parameters of NMR data, Unlike other methods, this algorithm makes full use of the rank-deficiency and Hankel properties of the prediction matrix composed of NMR data. Hence, it can estimate the signal parameters under low signal-to-noise ratio (SNR) by using a few data points. The effectiveness of the new algorithm is confirmed by computer simulations and it is tested by experimental data.
Keywords :
NMR spectroscopy; biological NMR; biological techniques; frequency-domain analysis; molecular biophysics; parameter estimation; proteins; Hankel properties; computer simulations; high-resolution subspace method; high-resolution technique; low signal-to-noise ratio; multidimensional NMR spectroscopy; multidimensional damped sinusoids sum; prediction matrix; protein structures determination; rank-deficiency properties; signal parameters; Computer simulation; Damping; Frequency estimation; Multidimensional systems; Nuclear magnetic resonance; Parameter estimation; Proteins; Signal to noise ratio; Spectroscopy; Testing; Algorithms; Computer Simulation; Image Enhancement; Magnetic Resonance Spectroscopy; Models, Theoretical; Signal Processing, Computer-Assisted;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
