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Proceedings Paper

Time-Varying Spectrum Estimation Via Multidimensional Filter Representation
Author(s): Moeness G. Amin; Maryanne T. Schiavoni
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Paper Abstract

Smoothing of Wigner distribution introduces two dimensional sequences which brings the theory of two-dimensional filter analysis and design to the one-dimensional time-varying spectrum estimation. In this paper, the region of support of the 2-D filters associated with the commonly used periodogram, averaged periodograms and Wigner estimators are defined and used to express through the singular value decomposition, the periodograms-based estimators as a linear combination of the Pseudo Wigner estimators (PWE). The PWE associated with the maximum singular value of the eigenvector expansion of the periodogram is viewed as the closest approximation between the two estimators. Error bounds are derived and simulations are performed to demonstrate the effects of limiting the expansion to the dominant singular vale es, i.e., using a reduced rank periodogram.

Paper Details

Date Published: 14 November 1989
PDF: 12 pages
Proc. SPIE 1152, Advanced Algorithms and Architectures for Signal Processing IV, (14 November 1989); doi: 10.1117/12.962297
Show Author Affiliations
Moeness G. Amin, Villanova University (United States)
Maryanne T. Schiavoni, General Electric Company (United States)


Published in SPIE Proceedings Vol. 1152:
Advanced Algorithms and Architectures for Signal Processing IV
Franklin T. Luk, Editor(s)

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