Selecting the modeling order for the ESPRIT high resolution method: an alternative approach
Abstract
High Resolution methods, such as the ESPRIT algorithm, perform an accurate representation of an harmonic signal as a sum of exponentially damped sinusoids. However, in coding applications, the signal must be represented with a minimum number of parameters. Unfortunately, it is well known that applying the ESPRIT algorithm with an under-estimated model order generates biased frequency estimates. In this paper, we propose a new method for selecting an appropriate modeling order, which minimizes this bias. This approach was applied to both synthetic and musical signals and outperformed the classical information theoretic criteria.
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