DocumentCode :
1842268
Title :
Shift and scale invariant detection
Author :
Zalubas, Eugene J. ; Neill, Jeffrey C O ; Williams, William J. ; Hero, Alfred O., III
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
Volume :
5
fYear :
1997
fDate :
21-24 Apr 1997
Firstpage :
3637
Abstract :
Different signal realizations generated from a given source may not appear the same. Time shifts, frequency shifts, and scales are among the signal variations commonly encountered. Time-frequency distributions (TFDs) covariant to time and frequency shifts and scale changes reflect these variations in a predictable manner. Based on such TFDs, representations invariant to these signal distortions are possible. Presented here are two approaches for discriminating between signal classes where within class translation and scale variation occur. The first method uses an auto-correlation followed by a scale transform to achieve the invariances. The second method treats the TFD as a two-dimensional probability density function and applies a transformation that removes the mean and variance to provide the shift and scale invariance. Each method employs discrimination mechanisms to yield powerful results
Keywords :
correlation methods; pattern classification; signal detection; signal representation; time-frequency analysis; transforms; TFDs; auto-correlation; discrimination mechanisms; frequency shifts; representations; scale invariant detection; scale transform; scale variation; shift detection; signal classes; signal distortions; signal realizations; time shifts; time-frequency distributions; two-dimensional probability density function; within class translation; Autocorrelation; Contracts; Distortion; Interference; Probability density function; Robustness; Signal generators; Testing; Time frequency analysis; Whales;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location :
Munich
ISSN :
1520-6149
Print_ISBN :
0-8186-7919-0
Type :
conf
DOI :
10.1109/ICASSP.1997.604654
Filename :
604654
Link To Document :
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