Exact ML estimation of spectroscopic parameters
In a paper on spectroscopic imaging published in this journal Spielman et al. (J. Magn. Reson. 79, 66-77 (1988)) made the important point that a priori information about the compounds present can and should be incorporated into the estimation of spectroscopic signal parameters. They proposed using the maximum likelihood (ML) approach for parameter estimation, but failed to incorporate properly the full a priori information that was assumed to be available. Consequently they ended up with a spectroscopic imaging method that is only a suboptimal approximation of the ML method. In this paper we derive the exact ML method, present a computationally efficient implementation of it (which is much faster than the direct implementation suggested by Spielman et al. for their suboptimal method), and illustrate numerically the performance gain that can be achieved over the method of Spielman et al. Copyright 2000 Academic Press.
Stoica
P
Department of Systems and Control, Uppsala University, Uppsala, SE-75103, Sweden.
Sundin
T