High-spectral-resolution time-frequency distribution kernels

Moeness G. Amin; William J. Williams

doi:10.1117/12.130938

30 November 1992 High-spectral-resolution time-frequency distribution kernels

Proceedings Volume 1770, Advanced Signal Processing Algorithms, Architectures, and Implementations III; (1992) https://doi.org/10.1117/12.130938
Event: San Diego '92, 1992, San Diego, CA, United States

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.

Citation Download Citation

Moeness G. Amin and William J. Williams "High-spectral-resolution time-frequency distribution kernels", Proc. SPIE 1770, Advanced Signal Processing Algorithms, Architectures, and Implementations III, (30 November 1992); https://doi.org/10.1117/12.130938

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