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Proceedings Paper

Comparison of the Gabor and short-time Fourier transforms for signal detection and feature extraction in noisy environments
Author(s): Louis Auslander; C. Buffalano; Richard S. Orr; Richard Tolimieri
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Paper Abstract

Effective signal detection and feature extraction in noisy environments generally depend on exploiting some knowledge of the signal. The short-time Fourier transform and the Gabor transform are two methods that exploit signal envelope information. This paper compares the two transforms and makes the case that the Gabor representation can often be more compact, and may require substantially less computation and storage in some applications. There is a sense in which the Gabor achieves a preferential trade of SNR for resolution, and because of this, one can also expect better signal recognition and feature reconstructions from the Gabor transform in the presence of noise.

Paper Details

Date Published: 1 November 1990
PDF: 18 pages
Proc. SPIE 1348, Advanced Signal Processing Algorithms, Architectures, and Implementations, (1 November 1990); doi: 10.1117/12.23480
Show Author Affiliations
Louis Auslander, DARPA and City Univ. of New Yo (United States)
C. Buffalano, Atlantic Aerospace Electronics Corp. (United States)
Richard S. Orr, Atlantic Aerospace Electronics Corp. (United States)
Richard Tolimieri, City Univ. of New York (United States)


Published in SPIE Proceedings Vol. 1348:
Advanced Signal Processing Algorithms, Architectures, and Implementations
Franklin T. Luk, Editor(s)

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