Spectral Parameter Estimation by an Iterative Quadratic Maximum Likelihood Method

✍ Scribed by Guang Zhu; W.Y. Choy; B.C. Sanctuary

• Publisher: Elsevier Science
• Year: 1998
• Tongue: English
• Weight: 149 KB
• Volume: 135
• Category: Article
• ISSN: 1090-7807
• DOI: 10.1006/jmre.1998.1539

✦ Synopsis

An iterative quadratic maximum likelihood (IQML) method is applied to spectral parameter estimation of 1D NMR data. A careful comparison of the linear prediction (LP) method based on the singular value decomposition, the total least squares (TLS) method, and IQML has clearly demonstrated that IQML is superior to both the LP and TLS methods in terms of the accuracy and bias of the estimation. The superiority of the IQML method lies in the fact that constraints on the NMR signal can easily be incorporated into the iterative process. The iterative quadratic maximum likelihood method can be used to analyze NMR data directly or to provide a starting point for further data refinement.