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Journal ArticleDOI

A minimal parameter adaptive notch filter with constrained poles and zeros

Arye Nehorai
- 01 Aug 1985 - 
- Vol. 33, Iss: 4, pp 983-996
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TLDR
A new algorithm is presented for adaptive notch filtering and parametric spectral estimation of multiple narrow-band or sine wave signals in an additive broad-band process and uses a special constrained model of infinite impulse response with a minimal number of parameters.
Abstract
A new algorithm is presented for adaptive notch filtering and parametric spectral estimation of multiple narrow-band or sine wave signals in an additive broad-band process. The algorithm is of recursive prediction error (RPE) form and uses a special constrained model of infinite impulse response (IIR) with a minimal number of parameters. The convergent filter is characterized by highly narrow bandwidth and uniform notches of desired shape. For sufficiently large data sets, the variances of the sine wave frequency estimates are of the same order of magnitude as the Cramer-Rao bound. Results from simulations illustrate the performance of the algorithm under a wide range of conditions.

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Citations
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The isolation of undistorted sinusoids in real time

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Adaptive instrumental variable methods for frequency estimation

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Proceedings ArticleDOI

Adaptive notch filtering in impulsive noise environment

TL;DR: An adaptive digital notch filter is considered for 50/60 Hz line frequency signal processing and soft and hard limiting are compared for Laplacian noise, and the effect of filtering is investigated for a signal with strong harmonic contents.
Patent

Detection and estimation of narrowband interference by matrix multiplication

TL;DR: In this paper, one or more processing units are programmed to select from among M tones in a frequency domain representation of a signal, a set of tones including at least a strongest tone (relative to background noise) and a tone adjacent thereto.
Proceedings ArticleDOI

Realtime implementation of an internal-model-principle signal identifier

TL;DR: An adaptive internal model principle based signal identification algorithm whose computational costs are low enough to allow a realtime implementation and how the equations can be decoupled into pairs of linear equations which have explicit solutions is shown.
References
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Journal ArticleDOI

Adaptive noise cancelling: Principles and applications

TL;DR: It is shown that in treating periodic interference the adaptive noise canceller acts as a notch filter with narrow bandwidth, infinite null, and the capability of tracking the exact frequency of the interference; in this case the canceller behaves as a linear, time-invariant system, with the adaptive filter converging on a dynamic rather than a static solution.
Book

Theory and application of digital signal processing

TL;DR: Feyman and Wing as discussed by the authors introduced the simplicity of the invariant imbedding method to tackle various problems of interest to engineers, physicists, applied mathematicians, and numerical analysts.
Journal ArticleDOI

Spectrum analysis—A modern perspective

TL;DR: In this paper, a summary of many of the new techniques developed in the last two decades for spectrum analysis of discrete time series is presented, including classical periodogram, classical Blackman-Tukey, autoregressive (maximum entropy), moving average, autotegressive-moving average, maximum likelihood, Prony, and Pisarenko methods.
Journal ArticleDOI

Analysis of recursive stochastic algorithms

TL;DR: It is shown how a deterministic differential equation can be associated with the algorithm and examples of applications of the results to problems in identification and adaptive control.
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