NDLI: A nonlinear error adaptive notch filter for separating two sinusoidal signals

Content Provider	IEEE Xplore Digital Library
Author	Douglas, S.C. Meng, T.H.-Y.
Copyright Year	1991
Description	Author affiliation: Inf. Syst. Lab., Stanford Univ., CA, USA (Douglas, S.C.; Meng, T.H.-Y.)
Abstract	For a primary input consisting of two sinusoids, the adaptive notch filter coefficients have sinusoidally varying components in steady-state which reduce the rejection at the notch frequency due to weight misadjustment. The authors present a simple modification of the adaptive notch filter that removes these sinusoidal variations, improves rejection, and enhances tracking performance. Using a general theory of non-mean-square error stochastic gradient adaptation, they show that the optimum nonlinear error algorithm adapts the system only when the instantaneous error magnitude is greater than the amplitude of the interfering sinusoid. This amplitude can be easily estimated at the output of the notch filter when the system nears convergence. To follow any slow changes in the interfering sinusoid amplitude, the authors introduce a time-varying error criterion to keep the algorithm optimal. Simulations show a 6-dB reduction of the excess mean-square error, a 10-13-dB improvement in rejection at the filter outputs, and an increase in adaptation speed near the solution over the least-mean-square adaptive notch filter when using this modified structure with a time-varying nonlinearity.
Starting Page	673
Ending Page	677
File Size	346633
Page Count	5
File Format	PDF
ISBN	0818624701
ISSN	10586393
DOI	10.1109/ACSSC.1991.186533
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1991-11-04
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Adaptive filters Frequency Least squares approximation Programmable control Adaptive control Vibration control Stochastic systems Information systems Laboratories Noise cancellation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Networks and Communications

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