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Proceedings Paper

High-spectral-resolution time-frequency distribution kernels
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Paper Abstract

A new class of time-frequency kernels is introduced. Members in this class satisfy the desired time-frequency distribution properties and simultaneously provide local autocorrelation functions (LAF) which are amenable to high resolution techniques over periods of stationarities. These high spectral resolution kernels map the sinusoids in time into damped/undamped sinusoidal bilinear data products over the LAF lag variable. The damped sinusoids represent cross-terms. Using SVD-based backward linear prediction techniques, the signal zeros, the cross-term zeros, and the extraneous zeros, respectively, lie on, outside, and inside the unit circle, providing a mechanism to distinguish between different types of components. It is shown that the binomial kernel introduced is a member of this class.

Paper Details

Date Published: 30 November 1992
PDF: 13 pages
Proc. SPIE 1770, Advanced Signal Processing Algorithms, Architectures, and Implementations III, (30 November 1992); doi: 10.1117/12.130938
Show Author Affiliations
Moeness G. Amin, Villanova Univ. (United States)
William J. Williams, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 1770:
Advanced Signal Processing Algorithms, Architectures, and Implementations III
Franklin T. Luk, Editor(s)

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