IMPROVED SIGNAL ENHANCEMENT PROCEDURES APPLIED TO EXPONENTIAL DATA MODELING

Various signal enhancement techniques have been proposed to improve sp ectral estimation of closely spaced sinusoids in the presence of noise . This correspondence exploits the filtering interpretation of some we ll-known SVD-based iterative algorithms for signal enhancement to furt her improve their performance. It is shown that the initial conditions that are used throughout the filtering process may considerably affec t the spectral characteristics of the signal. A strategy is proposed t o minimize these undesirable effects. The neu; method improves the per formance of fully automated magnetic resonance spectroscopy (MRS) quan titation.