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AM-FM separation using auditory-motivated filters

Content Provider	IEEE Xplore Digital Library
Author	Quatieri, T.F. Hanna, T.E. O'Leary, G.C.
Copyright Year	1993
Abstract	An approach to the joint estimation of sine-wave amplitude modulation (AM) and frequency modulation (FM) is described based on the transduction of frequency modulation into amplitude modulation by linear filters, being motivated by the hypothesis that the auditory system uses a similar transduction mechanism in measuring sine-wave FM. An AM-FM estimation algorithm is described that uses the amplitude envelope of the output of two transduction filters of piecewise-linear spectral shape. The piecewise-linear constraint is then relaxed, allowing a wider class of transduction-filter pairs for AM-FM separation under a monotonicity constraint on the filters' quotient. The particular case of Gaussian filters is shown to yield a closed-form solution to AM-FM estimation while gammatone filters, used as a simplified model of auditory filters, and measured auditory filters, although not leading to a solution in a closed form, provide for iterative AM-FM estimation. Solution stability analysis and error evaluation are performed and the FM transduction method is compared with the energy separation algorithm, based on the Teager energy operator, and the Hilbert transform method for AM-FM estimation. Finally, a generalization to two-dimensional (2-D) filters is described.
Starting Page	465
Ending Page	480
Page Count	16
File Size	568514
File Format	PDF
ISSN	10636676
Volume Number	5
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-09-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Nonlinear filters Frequency modulation Amplitude estimation Frequency estimation Amplitude modulation Piecewise linear techniques Yield estimation Auditory system Frequency measurement Shape measurement
Content Type	Text
Resource Type	Article
Subject	Acoustics and Ultrasonics Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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