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dr hab. inż. Michał Meller
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total: 58
Catalog Publications
Year 2023
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Active Control of Highly Autocorrelated Machinery Noise in Multivariate Nonminimum Phase Systems
PublicationIn this paper, a novel multivariate active noise control scheme, designed to attenuate disturbances with high autocorrelation characteristics and preserve background signals, is proposed. The algorithm belongs to the class of feedback controllers and, unlike the popular feedforward FX-LMS approach, does not require availability of a reference signal. The proposed approach draws its inspiration from the iterative learning control...
Year 2022
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A Control Theoretical Approach to Spectral Factorization is Unstable
PublicationLocal stability analysis of a recently proposed recursive feedback-based approach to spectral factorization is performed. The method is found not to give stability guarantees. Interestingly enough, its global behavior often allows one to obtain reasonable approximations of spectral factorizations if a suitable stopping criterion is employed.
Year 2021
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Active Suppression of Nonstationary Narrowband Acoustic Disturbances
PublicationIn this chapter, a new approach to active narrowband noise control is presented. Narrowband acoustic noise may be generated, among others, by rotating parts of electro-mechanical devices, such as motors, turbines, compressors, or fans. Active noise control involves the generation of “antinoise”, i.e., the generation of a sound that has the same amplitude, but the opposite phase, as the unwanted noise, which causes them to interfere...
Year 2020
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Iterative learning approach to active noise control of highly autocorrelated signals with applications to machinery noise
PublicationThis paper discusses the design and application of iterative learning control (ILC) and repetitive control (RC) for high modal density systems. Typical examples of these systems are structural and acoustical systems considered in active structural acoustic control (ASAC) and active noise control (ANC) applications. The application of traditional ILC and RC design techniques, which are based on a parametric system model, on systems...
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On DoA estimation for rotating arrays using stochastic maximum likelihood approach
PublicationThe flexibility needed to construct DoA estimators that can be used with rotating arrays subject to rapid variations of the signal frequency is offered by the stochastic maximum likelihood approach. Using a combination of analytic methods and Monte Carlo simulations, we show that for low and moderate source correlations the stochastic maximum likelihood estimator that assumes noncorrelated sources has accuracy comparable to the...
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On Radar DoA Estimation and Tilted Rotating Electronically Scanned Arrays
PublicationWe consider DoA estimation in a monopulse radar system employing a tilted rotating array. We investigate the case of nonzero steering angles, in which case the mapping between the target’s azimuth and elevation in the global coordinate system and their counterparts in the array local coordinate system becomes increasingly nonlinear and coupled. Since estimating the azimuth using coherently integrated signals might be difficult because...
Year 2019
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A concept of software extension of 3D low-PRF radar systems to 4D semi-medium-PRF radar systems
PublicationWe present a concept of software modification of three-dimensional (3D) radar systems, designed to work in the low pulse repetition frequency mode, that equips them with the ability to estimate the radial velocity and to properly measure the range of targets that are detected outside the radar’s instrumented range. Despite the fact that the proposed modifications are designed so as to require only minor changes in software, they...
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Adaptation of radar software to work with ambiguous distance measurement
PublicationA software extension for radar stations designed to work in the low-PRF mode that allows them to correctly measure range to targets outside of their instrumented range, is proposed. The solution does not require substantial modifications of the radar software. Additionally, we describe tools that allow one to simulate the output of a low-PRF radar observing targets that are outside its instrumented range. The proposed approach...
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Capon-like DoA estimator for rotating arrays
PublicationWe propose a nonparametric superresolution DoA estimator that is suitable for use with rotating arrays. The proposed method can be regarded as an extension of the Capon approach. We investigate its properties using computer simulations and present results obtained by processing of real world data.
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
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On Adaptive Spectrum Estimation of Multivariate Autoregressive Locally Stationary Processes
PublicationAutoregressive modeling is a widespread parametricspectrum estimation method. It is well known that, in the caseof stationary processes with unknown order, its accuracy canbe improved by averaging models of different complexity usingsuitably chosen weights. The paper proposes an extension of thistechnique to the case of multivariate locally stationary processes.The proposed solution is based on local autoregressive...
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Robustified estimators of radar elevation angle using a specular multipath model
PublicationWe consider the problem of estimating the elevation angle in the presence of multipath. The proposed method belongs to the class of maximum likelihood-like estimators and employs a modified specular reflection model that accounts for the uncertainty of the steering vector by assuming that they are subject to unknown deterministic perturbations with bounded norms. The analysis, performed using convex optimization methods, allows...
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Soft-decision schemes for radar estimation of elevation at low grazing angles
PublicationIn modern radars, the problem of estimating elevation angle at low grazing angles is typically solved using superresolution techniques. These techniques often require one to provide an estimate of the number of waveforms impinging the array, which one can accomplish using model selection techniques. In this paper, we investigate the performance of an alternative approach, based on the Bayesian-like model averaging. The Bayesian...
Year 2018
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On Bayesian Tracking and Prediction of Radar Cross Section
PublicationWe consider the problem of Bayesian tracking of radar cross section. The adopted observation model employs the gamma family, which covers all Swerling cases in a unified framework. State dynamics are modeled using a nonstationary autoregressive gamma process. The principal component of the proposed solution is a nontrivial gamma approximation, applied during the time update recursion. The superior performance of the proposed approach...
Year 2017
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Azimuth estimator for a rotating array radar with wide beam
PublicationThe problem of estimating azimuth in rotating array radar with a beam, wide in the azimuth plane, is considered. Under such setup the echo signal usually has a very low signal to noise ratio, but the number of observations is large, because of long dwell times. The proposed solution is based on the maximum likelihood approach, but it employs simplifications which facilitate its implementation in real time systems. Results, obtained...
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Estymacja azymutu w radarze z obracaną anteną i szeroką wiązką
PublicationRozważono problem estymacji azymutu w radarze z obracaną anteną, w którym zastosowano wiązkę o dużej szerokości w płaszczyźnie azymutu. Radary tego typu zwykle charakteryzują się niskim stosunkiem sygnału do szumu i dużą liczbą dostępnych obserwacji echa. Zaproponowane rozwiązanie jest oparte na metodzie największej wiarygodności, zmodyfikowanej w sposób, który pozwala na implementację estymatora w systemach czasu rzeczywistego....
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Experimental evaluation of estimator mean square error curve for cognitive tracking radar
PublicationTo make decisions, cognitive radar must rely on predictions of its own performance. In the literature, these predictions are usually based on some form of Cram\'er-Rao lower bound. This approach is scientifically sound, but it also brings a possibility of the cognitive controller overestimating radar performance. It therefore makes sense to back theoretical predictions with careful experiments which will verify their applicability....
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...
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On autoregressive spectrum estimation using the model averaging technique
PublicationThe problem of estimating spectral density of a nonstationary process satisfying local stationarity conditions is considered. The proposed solution is a two step procedure based on local autoregressive (AR) modeling. In the first step Bayesian-like averaging of AR models, differing in order, is performed. The main contribution of the paper is development of a new final-prediction-error-like statistic, which can be used to select...
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Radar time budget optimization subject to angle accuracy constraint via cognitive approach
PublicationThe problem of minimizing dwell time in multifunction phased array radar is considered. Target of interest is assumed to fluctuate according to a generalization of Swerling family and the parameters of fluctuation model are assumed to be known. The a'priori position of the target is uncertain. Optimization, whose variables include pulse count and array transmit beampattern, is carried out subject to achieving a desired accuracy...
Year 2016
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A self-optimization mechanism for generalized adaptive notch smoother
PublicationTracking of nonstationary narrowband signals is often accomplished using algorithms called adaptive notch filters (ANFs). Generalized adaptive notch smoothers (GANSs) extend the concepts of adaptive notch filtering in two directions. Firstly, they are designed to estimate coefficients of nonstationary quasi-periodic systems, rather than signals. Secondly, they employ noncausal processing, which greatly improves their accuracy and...
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Systemidentificationbasedapproachtodynamicweighing revisited
PublicationDynamicweighing,i.e.,weighingofobjectsinmotion,withoutstoppingthemonthe weighing platform,allowsonetoincreasetherateofoperationofautomaticweighing systems, usedinindustrialproductionprocesses,withoutcompromisingtheiraccuracy. Sincetheclassicalidentification-basedapproachtodynamicweighing,basedonthe second-ordermass–spring–dampermodeloftheweighingsystem,doesnotyieldsa- tisfactoryresultswhenappliedtoconveyorbelttypecheckweighers,severalextensionsof thistechniqueareexamined.Experimentsconfirmthatwhenappropriatelymodifiedthe identification-basedapproachbecomesareliabletoolfordynamicmassmeasurementin checkweighers.
Year 2015
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Active feedback noise control in the presence of impulsive disturbances
PublicationThe problem of active feedback control of a narrowband acoustic noise in the presence of impulsive disturbances is considered. It is shown that, when integrated with appropriately designed outlier detector, the proposed earlier feedback control algorithm called SONIC is capable of isolating and rejecting noise pulses. According to our tests this guarantees stable and reliable operation of the closed-loop noise cancelling...
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Frequency Guided Generalized Adaptive Notch Filtering - Tracking Analysis and Optimization
PublicationGeneralized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems, encountered e.g., in RF applications when Doppler effect takes place. Current state of the art GANFs can deliver highly accurate estimates of system variations’ frequency, but underperform in terms of accuracy of system coefficient estimates. The paper proposes a novel multistage GANF with improved coefficient...
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Multistage generalized adaptive notch filter with improved accuracy
PublicationGeneralized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems. Current state of the art GANFs can deliver highly accurate estimates of system variations’ frequency, but underperform in terms of accuracy of the coefficient estimates. The paper proposes a novel multistage GANF with accuracy improved in this aspect. The processing pipeline consists of three stages. The preliminary...
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Robust algorithm for active feedback control of narrowband noise
PublicationThe problem of active control of narrowband acoustic noise is considered. It is shown that the proposed earlier feedback control algorithm called SONIC (self-optimizing narrowband interference canceller), based on minimization of the L2-norm performance measure, can be re-derived using the L1 approach. The resulting robust SONIC algorithm is more robust to heavy-tailed measurement noise, such as the αlpha-stable noise, than the...
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Three solvers for MIMO noise radar clutter cancellation - a performance comparison
PublicationThe problem of canceling strong clutter echos in a MIMO noise radar is considered. Execution times of three algorithms is compared. The first solution is a standard Least Squares approach employing Cholesky decomposition of the transmitted signal sample autocorrelation matrix. The second approach is based on careful waveform design which guarantees that the signal sample autocorrelation matrix has Toeplitz structure. This enables...
Year 2014
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Adaptive filtering approach to dynamic weighing: a checkweigher case study
PublicationDynamic weighing, i.e., weighing of objects in motion, with out stopping them on the weighing platform, allows one to increase the rate of operation of automatic weighing systems used in industrial production processes without compromising their accuracy. The paper extends and compares two approaches to dynamic weighing, based on system identification and variable-bandwidth filtering, respectively. Experiments, carried on a conveyor...
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AUTOMATIC OPTIMIZATION OF ADAPTIVE NOTCH FILTER’S FREQUEN CY TRACKING
PublicationEstimation of instantaneous frequency of narrowband com- plex sinusoids is often performed using lightweight algo- rithms called adaptive notch filters. However, to reach high performance, these algorithms require careful tuning. The paper proposes a novel self-tuning layer for a recently intr o- ducedadaptive notch filtering algorithm. Analysis shows th at, under Gaussian random-walk type assumptions, the resultin g solution converges...
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Automatic Optimization Of Adaptive Notch Filter’s Frequency Tracking
PublicationEstimation of instantaneous frequency of narrowband com- plex sinusoids is often performed using lightweight algo- rithms called adaptive notch filters. However, to reach high performance, these algorithms require careful tuning. The paper proposes a novel self-tuning layer for a recently intr o- ducedadaptive notch filtering algorithm. Analysis shows th at, under Gaussian random-walk type assumptions, the resultin g solution converges...
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Dynamic mass measurement in checkweighers using a discrete time-variant low-pass filter
PublicationConveyor belt type checkweighers are complex mechanical systems consisting of a weighing sensor (strain gauge load cell, electrodynamically compensated load cell), packages (of different shapes, made of different materials) and a transport system (motors, gears, rollers). Disturbances generated by the vibrating parts of such a system are reflected in the signal power spectra in a form of strong spectral peaks, located usually in...
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Fast clutter cancellation for noise radars via waveform design
PublicationCanceling clutter is an important, but very expensive part of signal processing in noise radars. It is shown that considerable improvements can be made to a simple least squares canceler if minor constraints are imposed onto noise waveform. Using a combination of FPGA and CPU, the proposed scheme is capable of canceling both stationary clutter and moving targets in real-time, even for high sampling rates.
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Merging extremum seeking and self-optimizing narrowband interference canceller - overdetermined case
PublicationActive cancellation systems rely on destructive interference to achieve rejection of unwanted disturbances entering the system of interest. Typical practical applications of this method employ a simple single input, single output arrangement. However, when a spatial wavefield (e.g. acoustic noise or vibration) needs to be controlled, multichannel active cancellation systems arise naturally. Among these, the so-called overdetermined...
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Multichannel self-optimizing narrowband interference canceller
PublicationThe problem of cancellation of a nonstationary sinusoidal interference, acting at the output of an unknown multivariable linear stable plant, is considered. No reference signal is assumed to be available. The proposed feedback controller is a nontrivial extension of the SONIC (self-optimizing narrowband interference canceller) algorithm, developed earlier for single-input, single-output plants. The algorithm consists of two loops:...
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Self-tuning adaptive frequency tracker
PublicationAn automatic gain tuning algorithm is proposed for a recently introduced adaptive notch filter. Theoretical analysis and simulations show that, under Gaussian random-walk type assumptions, the proposed extension is capable of adjusting adaptation gains of the filter so as to minimize the mean-squared frequency tracking error without prior knowledge of the true frequency trajectory. A simplified one degree of freedom version of...
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Waveform design for fast clutter cancellation in noise radars
PublicationCanceling clutter is an important, but computation-ally intensive part of signal processing in noise radars. It is shown that considerable improvements can be made to a simple least squares canceler if minor constraints are imposed onto noise waveform. The proposed scheme is potentially capable of canceling clutter in real-time, even for high sampling rates.
Year 2013
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BUILT IN PERFORMANCE EVALUATION FOR AN ADAPTIVE NOTCH FILTER
PublicationThe problem of estimating instantaneous frequency of a non- stationary complexsinusoid (cisoid) buried in wideband no ise is considered. The proposed approach extends adaptive notc h filtering algorithm with a nontrivial performance assessme nt mechanism which can be used to optimize frequency tracking performance of the adaptive filter. Simulation results confi rm that the proposedextension allows one to improveaccuracyo f frequency...
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ESTIMATION OF NONSTATIONARY HARMONIC SIGNALS AND ITS APPLICATION TO ACTIVE CONTROL OF MRI NOISE
PublicationA new adaptive comb filtering algorithm, capable of tracking the fundamental frequency and amplitudes of different frequency components of a nonstationary harmonic signal embedded in white measurement noise, is proposed. Frequency tracking characteristics of the new scheme are studied analytically, proving (under Gaussian assumptions and optimal tuning) its statistical efficiency for quasi-linear frequency changes. Laboratory tests...
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Generalized adaptive comb filters/smoothers and their application to the identification of quasi-periodically varying systems and signals
PublicationThe problem of both causal and noncausal identification of linear stochastic systems with quasiharmonically varying parameters is considered. The quasi-harmonic description allows one to model nonsinusoidal quasi-periodic parameter changes. The proposed identification algorithms are called generalized adaptive comb filters/smoothers because in the special signal case they reduce down to adaptive comb algorithms used to enhance...
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Hybrid SONIC: joint feedforward–feedback narrowband interference canceler
PublicationSONIC (self-optimizing narrowband interference canceler) is an acronym of a recently proposed active noise control algorithm with interesting adaptivity and robustness properties. SONIC is a purely feedback controller, capable of rejecting nonstationary sinusoidal disturbances (with time-varying amplitude and/or frequency) in the presence of plant (secondary path) uncertainty. We show that although SONIC can work reliably without...
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Multiple-channel frequency-adaptive active vibration control using SONIC
PublicationSONIC (self-optimizing narrowband interference canceller) is an acronym of a new approach to rejection of sinusoidal disturbances acting at the output of a discretetime stable linear plant with unknown and possibly timevarying dynamics. The paper presents two frequency-adaptive extensions of the multivariate SONIC algorithm. The efficacy of the proposed solutions is tested using our laboratory-scale active vibration control plant.
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Parallel frequency tracking with built-in performance evaluation
PublicationThe problem of estimation of instantaneous frequency of a nonstationary complex sinusoid (cisoid) buried in wideband noise is considered. The proposed approach employs a bank of adaptive notch filters, extended with a nontrivial performance assessment mechanism which automatically chooses the best performing filter in the bank. Additionally, a computationally attractive method of implementing the bank is proposed. The new structure...
Year 2012
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Cheap Cancellation of Strong Echoes for Digital Passive and Noise Radars
PublicationThe problem of cancellation of strong, potentially nonstationary,echoes in noise radars and passive radars utilizing digitaltransmissions is considered. The proposed solution is a multi-stage procedure.Initial clutter estimates, obtained using the least mean squares(LMS) algorithm, are refined using specially designed filters, "matched"to spectral densities of targets and clutter. When the postprocessing filtersare noncausal, the...
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Generalized adaptive comb filter with improved accuracy and robustness properties
PublicationGeneralized adaptive comb lters can be used to identify/track parameters of quasi-periodically varying systems.In a special, signal case they reduce down to adaptive comblters, applied to elimination or extraction of nonstationarymulti-harmonic signals buried in noise. We proposea new algorithm which combines, in an adaptive way, resultsyielded by several, simultaneously working generalizedadaptive comb lters. Due to its highly...
Year 2011
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Identification of quasi-periodically varying systems with quasi-linear frequency changes
PublicationThe problem of identification of linear quasi-periodically varying systems is considered. This problem can be solved using generalized adaptive notch filtering (GANF) algorithms. It is shown that accuracy of system parameter estimation can be increased if the results obtained from GANF are further processed using a cascade of appropriately designed filters. The resulting generalized adaptive notch smoothing (GANS) algorithms can...
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New Algorithms for Adaptive Notch Smoothing
PublicationThe problem of extraction/elimination of a nonstationary complex sinusoidal signal buried in noise is considered. This problem is usually solved using adaptive notch filtering (ANF)algorithms. It is shown that accuracy of signal estimation can be increased if the results obtained from ANF are further processed using a cascade of appropriately designed filters. The resulting adaptive notch smoothing (ANS) algorithms can be employed...
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On the instantaneous frequency smoothing for signals with quasi-linear frequency changes
PublicationThe problem of estimation of the slowly-varying instantaneous frequency of a nonstationary complex sinusoidal signal buried in noise is considered. This problem is usually solved using frequency tracking algorithms. It is shown that the accuracy of frequency estimates can be considerably increased if the results yielded by the frequency tracker are further processed using the appropriately designed filters. The resulting frequency...
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Self-optimizing narrowband interference canceller - can reference signal help?
PublicationSONIC (Self-Optimizing Narrowband Interference Canceller) is an acronym of the recently proposed active noise control algorithm with interesting adaptivity and robustness properties. SONIC is a purely feedback controller, capable of rejecting nonstationary sinusoidal disturbances (with time-varying amplitudes and/or frequencies) in the presence of plant (secondary path) uncertainties. We show that even though SONIC can work reliably...
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Semi-adaptive feedback active control of MRI noise
PublicationA feedback controller is proposed for cancellation of magnetic resonance imaging (MRI) noise. The design of the controller takes into account specific features of the MRI noise signal. Simulation results show that a considerable rejection rate of the MRI noise can be obtained.
Year 2010
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An improved frequency estimator for an adaptive active noise control scheme
PublicationAn improved frequency tracker is proposed for the recently introduced self optimizing narrowband interference canceller (SONIC). The scheme is designed for disturbances with quasi-linear frequency modulation and, under second-order Gaussian random-walk assumption, can be shown to be statistically efficient. One real-world experiment and several simulations show that a considerable improvement in disturbance rejection may be achieved...
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