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Proceedings Paper

Generalized scale transforms
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Paper Abstract

We are presenting a new class of transforms which facilitates the processing of signals that are nonlinearly stretched or compressed in time. We refer to nonlinear stretching and compression as warping. While the magnitude of the Fourier transform is invariant under time shift operations, and the magnitude of the scale transform is invariant under (linear) scaling operations, the new class of transforms is magnitude invariant under warping operations. The new class contains the Fourier transform and the scale transform as special cases. Important theorems, like the convolution theorem for Fourier transforms, are generalized into theorems that apply to arbitrary members of the transform class. Cohen's class of time-frequency distributions is generalized to joint representations in time and arbitrary warping variables. Special attention is paid to a modification of the new class of transforms that maps an arbitrary time-frequency contour into an impulse in the transforms that maps an arbitrary time-frequency contour into an impulse in the transform domain. A chirp transform is derived as an example.

Paper Details

Date Published: 2 November 1999
PDF: 11 pages
Proc. SPIE 3807, Advanced Signal Processing Algorithms, Architectures, and Implementations IX, (2 November 1999); doi: 10.1117/12.367663
Show Author Affiliations
Robert M. Nickel, Univ. of Michigan (United States)
William J. Williams, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 3807:
Advanced Signal Processing Algorithms, Architectures, and Implementations IX
Franklin T. Luk, Editor(s)

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