Journal ArticleDOI
A minimal parameter adaptive notch filter with constrained poles and zeros
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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.read more
Citations
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Journal ArticleDOI
The feedback adaptive line enhancer: a constrained IIR adaptive filter
J. Chang,J.R. Glover +1 more
TL;DR: A new adaptive line enhancer structure, called the Feedback ALE (FALE), is presented and is shown to be a constrained W adaptive filter that gives a higher sine-to-broadband ratio gain and smaller sine estimation error than does an equal-order ALE.
Journal ArticleDOI
Adaptive notch filters are local adaptive observers
Riccardo Marino,Patrizio Tomei +1 more
TL;DR: In this article, the adaptive notch filter (ANF) was shown to be equivalent to the orthogonal signal generator (OSG) in terms of local convergence properties for the estimation errors, that is, the convergence to zero is guaranteed provided that their initial error is sufficiently small.
Journal ArticleDOI
Adaptive Filters for Frequency Estimate of Heterodyne Doppler Lidar Returns: Recursive Implementation and Quality Control
TL;DR: The authors propose use of a recursive implementation of an adaptive filter for frequency estimate coupled with a QC that combines a statistical test on the signal energy filtered out as proposed by Rye and Hardesty and a persistency criterion (PC).
Journal ArticleDOI
Direct frequency estimation based adaptive algorithm for a second-order adaptive FIR notch filter
Rachu Punchalard,A. Lorsawatsiri,W. Loetwassana,Jeerasuda Koseeyaporn,Paramote Wardkein,A. Roeksabutr +5 more
TL;DR: The direct frequency estimation based adaptive algorithm for a second-order adaptive finite impulse response (FIR) notch filter (AFNF) is proposed and employs the bias removal technique to remove the bias existing in the estimated parameter.
Journal ArticleDOI
A New Adaptive Notch Filtering Algorithm Based on Normalized Lattice Structure with Improved Mean Update Term
TL;DR: It is proved that the ACLA has faster convergence speed than the conventional lattice-based algorithms and the mean update term of the A CLA is always larger than that of the conventional algorithms.
References
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Journal ArticleDOI
Adaptive noise cancelling: Principles and applications
Bernard Widrow,J.R. Glover,John M. McCool,J. Kaunitz,C.S. Williams,R.H. Hearn,James R. Zeidler,Jr. Eugene Dong,R.C. Goodlin +8 more
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
Steven Kay,S.L. Marple +1 more
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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