Title :
A Shift Invariance-Based Order-Selection Technique for Exponential Data Modelling
Author :
Papy, J-M. ; De Lathauwer, L. ; Van Huffel, Sabine
fDate :
7/1/2007 12:00:00 AM
Abstract :
This paper presents a new subspace-based technique for automatic detection of the number of exponentially damped sinusoids. It consists in studying the shift-invariance of the dominant subspace of the Hankel data matrix. No threshold setting and no penalization terms are necessary. This model-based method, easy to implement, can be plugged into most subspace-based harmonic retrieval algorithms.
Keywords :
Hankel matrices; harmonics; signal processing; singular value decomposition; Hankel data matrix; automatic detection; exponential data modelling; exponentially damped sinusoids model; shift invariance-based order-selection technique; singular value decomposition; subspace-based harmonic retrieval algorithms; Biomedical signal processing; Least squares methods; Magnetic materials; Magnetic noise; Matrix decomposition; Nuclear magnetic resonance; Signal processing algorithms; Singular value decomposition; US Government; Exponentially damped sinusoids; harmonic retrieval; order selection; singular value decomposition; subspace; total least squares;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2006.891324
