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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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Journal ArticleDOI

A Study on Least Mean p-th Adaptive Notch Filter

TL;DR: This paper proposes a least mean p-th adaptive notch filter that has a cost function of E[ep(n), where e(n) is the estimation error, and the convergence performance of the estimation accuracy is verified by the computer simulation.
Proceedings ArticleDOI

A novel memoryless nonlinear gradient algorithm for a second-order adaptive IIR notch filter

TL;DR: The gradient linearization, Taylor series expansion and calculus of variations are employed to derive a memoryless nonlinear gradient function for a second-order adaptive IIR notch filter, which improves the estimation performance considerably.

Adaptive notch filters for acoustic howling suppression

TL;DR: In this article, a method for the suppression of acoustic howling is developed, based on adaptive notch filters (ANF) with regulariza- tion (RANF), which features three RANFs working in parallel to achieve frequency tracking, howling detection and suppression.
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Hilbert transform of a constant envelope signal using the time-warping technique

TL;DR: The method is based on a time-warping technique which transforms the constant envelope signal into a harmonic one, simply by delaying the harmonic signal by a quarter of its period.
Proceedings ArticleDOI

A New Model for Applying Extended Kalman Filtering to Extract Harmonic Signals from Noisy Measurements

TL;DR: This paper starts by deriving a differential equation that explicitly includes time varying amplitude and frequency, and it is shown that this can be reduced to a Bessel's equation of order 1/2 that has a closed form solution.
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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