NDLI: Response of the adaptive line enhancer to chirped sinusoids

Content Provider	IEEE Xplore Digital Library
Author	Treichler, J.R.
Copyright Year	1978
Description	Author affiliation: ARGO Systems, Inc., Sunnyvale, California (Treichler, J.R.)
Abstract	The Adaptive Line Enhancer (ALE) was first described by Widrow et al, as a practical on-line technique for separating the coherent components from the incoherent components of an input signal. Subsequent work has shown this same adaptive filtering structure to be applicable to maximum entropy spectral estimation, predictive deconvolution, and narrowband interference rejection, as well as other applications which have historically used matrix inversion and Levinson's algorithm techniques. While an often cited advantage of adaptive filtering is its tolerance of slowly time-varying input statistics, the existing analyses of the ALE have concentrated on the stationary case. This paper extends these results, applying the theory to the case of inputs containing sinusoids whose frequencies slowly vary in time. This is approached by developing a time-varying eigenvalue-eigenvector description of the expected filter impulse response vector which holds for any slowly nonstationary input. These results are then used to predict the expected impulse response vector for the ALE input of stationary white noise plus a sinusoid with linearly swept frequency. The response of the ALE for this particular input signal provides useful benchmarks for dealing with more complex forms of frequency modulation.
Starting Page	1368
Ending Page	1373
File Size	455746
Page Count	6
File Format	PDF
DOI	10.1109/CDC.1978.268141
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1979-01-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Line enhancers Chirp Adaptive filters Frequency Entropy Deconvolution Narrowband Interference Filtering algorithms Statistical analysis
Content Type	Text
Resource Type	Article

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