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prof. dr hab. inż. Maciej Niedźwiecki
Employment
- Professor at Department of Marine Electronic Systems
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total: 108
Catalog Publications
Year 2009
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A new approach to active noise and vibration control - [Part I: the known frequency case]
PublicationThis paper presents a new approach to rejection of complex-valued sinusoidal disturbances acting at the output of a discrete-time stable linear plant with unknown dynamics. It is assumed that the frequency of the sinusoidal disturbance is known, and that the output signal is contaminated with wideband measurement noise. The disturbance rejection control rule is first derived and analyzed for a nominal plant model, different from...
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A new approach to active noise and vibration control - [Part II: unknown frequency case]
PublicationThis paper presents a new approach to rejection of complex-valued sinusoidal disturbances acting at the output of a discrete-time stable linear plant with unknown and possibly timevarying dynamics. It is assumed that both the instantaneous frequency of the sinusoidal disturbance and its amplitude may be slowly varying with time and that the output signal is contaminated with wideband measurement noise. It is not assumed that a...
Year 2020
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A new look at the statistical identification of nonstationary systems
PublicationThe paper presents a new, two-stage approach to identification of linear time-varying stochastic systems, based on the concepts of preestimation and postfiltering. The proposed preestimated parameter trajectories are unbiased but have large variability. Hence, to obtain reliable estimates of system parameters, the preestimated trajectories must be further filtered (postfiltered). It is shown how one can design and optimize such...
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A New Method of Noncausal Identification of Time-varying Systems
PublicationThe paper shows that the problem of noncausal identification of a time-varying FIR (finite impulse response) sys- tem can be reformulated, and solved, as a problem of smoothing of the preestimated parameter trajectories. Characteristics of the smoothing filter should be chosen so as to provide the best trade- off between the bias and variance of the resulting estimates. It is shown that optimization of the smoothing operation can...
Year 2007
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A simple way of increasing estimation accuracy of generalized adaptive notch filters
PublicationGeneralized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. It is shown that frequency biases, which arisein generalized adaptive notch filtering algorithms, can be significantly reduced by incorporating in the adaptive loop an appropriately chosen decision delay. The resulting performance...
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Generalized adaptive notch filters with frequency debiasing for tracking of polynomial phase systems
PublicationGeneralized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. For general patterns of frequency variation the generalized adaptive notch filtering algorithms yield biased frequency estimates. We show that when system frequencies change slowly in a smooth way, the estimation bias can...
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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Automated Detection of Sleep Apnea and Hypopnea Events Based on Robust Airflow Envelope Tracking in the Presence of Breathing Artifacts. - [IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS]
PublicationThe paper presents a new approach to detection of apnea/hypopnea events, in the presence of artifacts and breathing irregularities, from a single channel airflow record. The proposed algorithm, based on a robust envelope detector , identifies segments of signal affected by a high amplitude mo d- ulation corresponding to apnea/hypopnea events. It is show n that a robust airflow envelope - free of breathing artifacts - improves effectiveness...
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Elimination of Impulsive Disturbances From Stereo Audio Recordings Using Vector Autoregressive Modeling and Variable-order Kalman Filtering
PublicationThis paper presents a new approach to elimination of impulsive disturbances from stereo audio recordings. The proposed solution is based on vector autoregressive modeling of audio signals. Online tracking of signal model parameters is performed using the exponential ly weighted least squares algo- rithm. Detection of noise pulses an d model-based interpolation of the irrevocably distorted sampl es is realized using an adaptive, variable-order...
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...
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Application of regularized Savitzky–Golay filters to identification of time-varying systems
PublicationSavitzky–Golay (SG) filtering is a classical signal smoothing technique based on the local least squares approximation of the analyzed signal by a linear combination of known functions of time (originally — powers of time, which corresponds to polynomial approximation). It is shown that the regularized version of the SG algorithm can be successfully applied to identification of time-varying finite impulse response (FIR) systems....
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Decoupled Kalman filter based identification of time-varying FIR systems
PublicationWhen system parameters vary at a fast rate, identification schemes based on model-free local estimation approaches do not yield satisfactory results. In cases like this, more sophisticated parameter tracking procedures must be used, based on explicit models of parameter variation (often referred to as hypermodels), either deterministic or stochastic. Kalman filter trackers, which belong to the second category, are seldom used in...
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Identification of Fast Time-varying Communication Channels Using the Preestimation Technique
PublicationAccurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state-of-the-art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...
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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Automated detection of sleep apnea and hypopnea events based on robust airflow envelope tracking
PublicationThe paper presents a new approach to detection of apnea/hypopnea events, in the presence of artifacts and breathing irregularities, from a single-channel airflow record. The proposed algorithm identifies segments of signal affected by a high amplitude modulation corresponding to apnea/hypopnea events. It is shown that a robust airflow envelope—free of breathing artifacts—improves effectiveness of the diagnostic process and allows...
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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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Elimination of impulsive disturbances from archive audio files – comparison of three noise pulse detection schemes
PublicationThe problem of elimination of impulsive disturbances (such as clicks, pops, ticks, crackles, and record scratches) from archive audio recordings is considered and solved using autoregressive modeling. Three classical noise pulse detection schemes are examined and compared: the approach based on open-loop multi-step-ahead signal prediction, the approach based on decision-feedback signal prediction, and the double threshold approach,...
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Elimination of impulsive disturbances from stereo audio recordings
PublicationThis paper presents a new approach to elimination of impulsive disturbances from stereo audio recordings. The proposed solution is based on vector autoregressive modeling of audio signals. On-line tracking of signal model parameters is performed using the stability-preserving Whittle-Wiggins-Robinson algorithm with exponential data weighting. Detection of noise pulses and model-based interpolation of the irrevocably distorted samples...
Year 2022
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Adaptive identification of sparse underwater acoustic channels with a mix of static and time-varying parameters
PublicationWe consider identification of sparse linear systems with a mix of static and time-varying parameters. Such systems are typical in underwater acoustics (UWA), for instance, in applications requiring identi- fication of the acoustic channel, such as UWA communications, navigation and continuous-wave sonar. The recently proposed fast local basis function (fLBF) algorithm provides high performance when identi- fying time-varying systems....
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Adaptive Identification of Underwater Acoustic Channel with a Mix of Static and Time-Varying Parameters
PublicationWe consider the problem of identification of communication channels with a mix of static and time-varying parameters. Such scenarios are typical, among others, in underwater acoustics. In this paper, we further develop adaptive algorithms built on the local basis function (LBF) principle resulting in excellent performance when identifying time-varying systems. The main drawback of an LBF algorithm is its high complexity. The subsequently...
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Finite-window RLS algorithms
PublicationTwo recursive least-squares (RLS) adaptive filtering algorithms are most often used in practice, the exponential and sliding (rectangular) window RLS algorithms. This popularity is mainly due to existence of low-complexity versions of these algorithms. However, these two windows are not always the best choice for identification of fast time-varying systems, when the identification performance is most important. In this paper, we...
Year 2017
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Akaike's final prediction error criterion revisited
PublicationWhen local identification of a nonstationary ARX system is carried out, two important decisions must be taken. First, one should decide upon the number of estimated parameters, i.e., on the model order. Second, one should choose the appropriate estimation bandwidth, related to the (effective) number of input-output data samples that will be used for identification/ tracking purposes. Failure to make the right decisions results...
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Detection of impulsive disturbances in archive audio signals
PublicationIn this paper the problem of detection of impulsive disturbances in archive audio signals is considered. It is shown that semi-causal/noncausal solutions based on joint evaluation of signal prediction errors and leave-one-out signal interpolation errors, allow one to noticeably improve detection results compared to the prediction-only based solutions. The proposed approaches are evaluated on a set of clean audio signals contaminated...
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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Easy recipes for cooperative smoothing
PublicationIn this paper we suggest how several competing signal smoothers, differing in design parameters, or even in design principles, can be combined together to yield a better and more reliable smoothing algorithm. The proposed heuristic, but statistically well motivated, fusion mechanism allows one to combine practically all kinds of smoothers, from simple local averaging or order statistic filters, to parametric smoothers designed...
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Generalized adaptive notch smoothing revisited
PublicationThe problem of identification of quasi-periodically varying dynamic systems is considered. This problem can be solved using generalized adaptive notch filtering (GANF) algorithms. It is shown that the accuracy of parameter estimates can be significantly increased if the results obtained from GANF are further processed using a cascade of appropriately designed filters. The resulting generalized adaptive notch smoothing (GANS) algorithm...
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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Elimination of Impulsive Disturbances From Archive Audio Signals Using Bidirectional Processing
PublicationIn this application-oriented paper we consider the problem of elimination of impulsive disturbances, such as clicks, pops and record scratches, from archive audio recordings. The proposed approach is based on bidirectional processing—noise pulses are localized by combining the results of forward-time and backward-time signal analysis. Based on the results of specially designed empirical tests (rather than on the results of theoretical analysis),...
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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...
Year 2012
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Elimination of clicks from archive speech signals using sparse autoregressive modeling
PublicationThis paper presents a new approach to elimination of impulsivedisturbances from archive speech signals. The proposedsparse autoregressive (SAR) signal representation is given ina factorized form - the model is a cascade of the so-called formantfilter and pitch filter. Such a technique has been widelyused in code-excited linear prediction (CELP) systems, as itguarantees model stability. After detection of noise pulses usinglinear...
Year 2005
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Estimation and tracking of complex-valued quasi-periodically varying systems
PublicationW artykule rozważany jest problem identyfikacji obiektów o parametrach zmieniających się w sposób pseudookresowy. Przedstawiono w nim algorytm oparty o metodę funkcji bazowych umożliwiający śledzenie takich obiektów oraz pokazano atrakcyjne z punktu widzenia złożoności obliczeń jego wersje zdekomponowane. Przydatność rozważanych algorytmów uzasadniono porównując je z rozwiązaniami innych autorów.
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Generalized adaptive notch and comb filters for identification of quasi-periodically varying systems
PublicationW artykule wprowadzono pojęcie obiektów pseudookresowych o parametrach będących liczbami rzeczywistymi. Pokazanometody oparte na metodzie funkcji bazowych pozwalające na identyfikację takich obiektów. Przedstawiono związekpomiędzy zaprojektowanymi algorytmami a klasycznymi filtrami wycinającymi typu notch.
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Identification of quasi-periodically varying systems using the combined nonparametric/parametric approach
PublicationW artykule przedstawiono tzw. uogólniony periodogram pozawlający na określenie liczby funkcji bazowych opisujących obiekt o parametrach zmieniających się w sposób pseudookresowy. Pokazano w jaki sposób określić wartości początkowe dla algorytmów opartych na metodzie funkcji bazowych na jego podstawie. Skuteczność zaproponowanych metod zilustrowano przykładami.
Year 2023
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Fast Algorithms for Identification of Time-Varying Systems with Both Smooth and Discontinuous Parameter Changes
PublicationThe problem of noncausal identification of a time-varying linear system subject to both smooth and occasional jump-type changes is considered and solved using the preestimation technique combined with the basis function approach to modeling the variability of system parameters. The proposed estimation algorithms yield very good parameter tracking results and are computationally attractive.
Year 2003
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Fast algorithms for identyfication of periodiccaly varying systems.
PublicationPraca dotyczy identyfikacji obiektów o parametrach zmieniających się w sposób okresowy. Zaproponowane algorytmy śledzenia parametrów cechują się niską złożonością obliczeniową, typową dla podejścia gradientowego a zarazem wysoką jakością śledzenia typową dla złożonych algorytmów opartych na metodzie funkcji bazowych.
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Gradient based basis function algorithms for identification of quasi periodically varying processes.
PublicationW pracy przedstawiono problem identyfikacji systemów, których parametry zmieniają się w sposób pseudookresowy. Pokazano sposób, w jaki można modelować takie systemy przy zastosowaniu metody harmonicznych funkcji bazowych.Przedstawiono dwa sposoby dekompozycji (struktura szeregowa i równoległa) takich układów na elementy związane z poszczególnymi funkcjami bazowymi. Zaprezentowany został sposób śledzenia częstotliwości funkcji...
Year 2019
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Fast Basis Function Estimators for Identification of Nonstationary Stochastic Processes
PublicationThe problem of identification of a linear nonsta-tionary stochastic process is considered and solved using theapproach based on functional series approximation of time-varying parameter trajectories. The proposed fast basis func-tion estimators are computationally attractive and yield resultsthat are better than those provided by the local least squaresalgorithms. It is shown that two...
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Fully Adaptive Savitzky-Golay Type Smoothers
PublicationThe problem of adaptive signal smoothing is consid-ered and solved using the weighted basis function approach. Inthe special case of polynomial basis and uniform weighting theproposed method reduces down to the celebrated Savitzky-Golaysmoother. Data adaptiveness is achieved via parallel estimation.It is shown that for the polynomial and harmonic bases andcosinusoidal weighting sequences, the competing signal estimatescan be computed...
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Generalized Savitzky–Golay filters for identification of nonstationary systems
PublicationThe problem of identification of nonstationary systems using noncausal estimation schemes is consid-ered and a new class of identification algorithms, combining the basis functions approach with localestimationtechnique,isdescribed.Unliketheclassicalbasisfunctionestimationschemes,theproposedlocal basis function estimators are not used to obtain interval approximations of the parametertrajectory, but provide a sequence of point...
Year 2002
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Fast recursive basis function estimators for identification of time-varying processes
PublicationW pracy wprowadzono nową kategorię filtrów adaptacyjnych opartych na metodzie funkcji bazowych i wykorzystujących koncepcję postfiltracji. Proponowane algorytmy pozwalają połączyć niską złożoność obliczeniową i dobre właściwości śledzące.
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Increasing accuracy of frequency estimation by decimation. W: [CD-ROM]EUSIPCO 2002. XI European Signal Processing Conference. Toulouse, France, September 3-6, 2002. [B.m.]: New Medias**2002 [4 s. 3 rys. bibliogr. 6 poz.] Page numbers in the proceedings: Volume 3, s. 135-138. Zwiększanie dokładności estymacji częstotliwości poprzez decymację.
PublicationArtykuł rozważa problem estymacji częstotliwości zaszumionego, sinusoidalne-go sygnału zespolonego. Częstotliwość wyznaczana jest w oparciu o autoregre-syjny model sygnału. W pracy wykazano, że wprowadzenie decymacji sygnału po-zwala na redukcję rzędu modelu autoregresyjnego, a tym samym powoduje znacz=ne zmniejszenie złożoności obliczeniowej metody.
Year 2008
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From the multiple frequency tracker to the multiple frequency smoother
PublicationThe problem of extraction/elimination of nonstationary sinusoidalsignals from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF)algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS)algorithm...
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Generalized adaptive notch smoothers for real-valued signals and systems
PublicationSystems with quasi-periodically varying coefficients can be tracked using the algorithms known as generalized adaptive notch filters (GANFs). GANF algorithms can be considered an extension, to the system case, of classical adaptive notch filters (ANFs). We show that estimation accuracy of the existing algorithms, as well as their robustness to the choice of design parameters, can be considerably improved by means of compensating...
Year 2006
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Generalized adaptive notch filter with a self-optimization capability
PublicationW pracy przedstawiono samonastrajalny wariant tzw. uogólnionego adaptacyjnego filtru wycinającego. Automatycznym strojeniem objęte są dwa współczynniki wzmocnienia adaptacji, odpowiedzialne za śledzenie amplitud i częstotliwości parametrów identyfikowanego obiektu.
Year 2016
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High-Precision FIR-Model-Based Dynamic Weighing System
PublicationConveyor belt-type checkweighers are increasingly popular components of modern production lines. They are used to assess the weight of the produced items in motion, i.e., without stopping them on the weighing platform. The main challenge one faces when designing a dynamic weighing system is providing high measurement accuracy, especially at high conveyor belt speeds. The approach proposed in this paper can be characterized as a...
Year 2018
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublicationThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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Identification of nonstationary processes using noncausal bidirectional lattice filtering
PublicationThe problem of off-line identification of a nonstationary autoregressive process with a time-varying order and a time-varying degree of nonstationarity is considered and solved using the parallel estimation approach. The proposed parallel estimation scheme is made up of several bidirectional (noncausal) exponentially weighted lattice algorithms with different estimation memory and order settings. It is shown that optimization of...
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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