Frequency-selective techniques based on singular value decomposition (SVD), total least squares (TLS), and bandpass filtering

Hua Chen; Sabine Van Huffel; Joos Vandewalle

doi:10.1117/12.190871

28 October 1994 Frequency-selective techniques based on singular value decomposition (SVD), total least squares (TLS), and bandpass filtering

Hua Chen, Sabine Van Huffel, Joos Vandewalle

Author Affiliations +

Proceedings Volume 2296, Advanced Signal Processing: Algorithms, Architectures, and Implementations V; (1994) https://doi.org/10.1117/12.190871
Event: SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, 1994, San Diego, CA, United States

Abstract

Much research has focused on estimating the parameters of a sum of exponentially damped sinusoids. In some applications, such as nuclear magnetic resonance signal processing, only a few of the sinusoids are of interest. This paper presents some new frequency-selective techniques for estimating the parameters of sinusoids within a specified frequency region using a subspace and SVD-based estimation algorithm and an FIR filter matrix. The applicable estimation algorithms in this technique are the linear prediction method, the matrix pencil method, Kung et al.'s method and its total-least-squares variant, called the HTLS method. The benefits of the frequency-selective technique combined with the HTLS estimation method are confirmed through simulations.

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Hua Chen, Sabine Van Huffel, and Joos Vandewalle "Frequency-selective techniques based on singular value decomposition (SVD), total least squares (TLS), and bandpass filtering", Proc. SPIE 2296, Advanced Signal Processing: Algorithms, Architectures, and Implementations V, (28 October 1994); https://doi.org/10.1117/12.190871

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