Publikacje
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wszystkich: 196
Katalog Publikacji
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Regularized Identification of Time-Varying FIR Systems Based on Generalized Cross-Validation
PublikacjaA new regularization method is proposed and applied to identification of time-varying finite impulse response systems. We show, that by a careful design of the regularization constraint, one can improve estimation results, especially in the presence of strong measurement noise. We also show that the the most appropriate regularization gain can be found by direct optimization of the generalized cross-validation criterion.
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On the preestimation technique and its application to identification of nonstationary systems
PublikacjaThe problem of noncausal identification of a nonstationary stochastic FIR (finite impulse response) sys- tem is reformulated, and solved, as a problem of smoothing of preestimated parameter trajectories. Three approaches to preestimation are critically analyzed and compared. It is shown that optimization of the smoothing operation can be performed adaptively using the parallel estimation technique. The new approach is computationally...
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A New Method of Noncausal Identification of Time-varying Systems
PublikacjaThe 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...
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Identification of nonstationary processes using noncausal bidirectional lattice filtering
PublikacjaThe 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...
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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublikacjaThe problem of identification of nonstationary multivariate autoregressive processes using noncausal local estimation schemes is considered and a new approach to joint selection of the model order and the estimation bandwidth is proposed. The new selection rule, based on evaluation of pseudoprediction errors, is compared with the previously proposed one, based on the modified Akaike’s final prediction error criterion.
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Soft-decision schemes for radar estimation of elevation at low grazing angles
PublikacjaIn 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...
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Parametryczna estymacja widma lokalnie stacjonarnych procesów losowych
PublikacjaW niniejszej pracy doktorskiej opisano nowe metody estymacji widmowej gestosci mocy niestacjonarnych procesów stochastycznych. Przedstawione w rozprawie rozwiazania, takie jak dwukierunkowy algorytm drabinkowy z zapominaniem wykładniczym oraz metoda usredniania modeli umozliwiaja precyzyjna estymacje charakterystyk widmowych. Przeprowadzone symulacje potwierdziły, ze opracowane algorytmy daja zadowalajace rezultaty zarówno w przypadku...
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A concept of software extension of 3D low-PRF radar systems to 4D semi-medium-PRF radar systems
PublikacjaWe 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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Simple stable discrete-time generalised predictive control with anticipated filtration of control error
PublikacjaPraca dotyczy uogólnionego sterowania predykcyjnego w czasie dyskretnym z antypacyjną filtracją błędu sterowania. Pokazano, iż przy spełnieniu pewnych warunków rozwiązanie problemu syntezy optymlanego regulatora predykcyjnego zawsze istnieje oraz prowadzi do stabilnego zamkniętego układu sterowania o określonych własnościach dynamicznych. W pracy rozważano także problem syntezy regulatora predykcyjnego dla modeli sterowania obiektów...
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Robust design in delta domain for SISO plants: PI and PID controllers
PublikacjaW pracy przedstawiono zunifikowaną metodę numerycznie odpornej syntezy sterowników (regulatorów) działających w dyskretnym czasie w układach sterowania skalarnymi obiektami czasu ciągłego. Wykorzystano dyskretnoczasowe modele takich obiektów, oparte na tak zwanym operatorze delta, charakteryzującym się korzystnymi odpornościowymi cechami w przypadku stosowania dostatecznie małych wartości okresu próbkowania przetwarzanych sygnałów....
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A J-lossless coprime factorisation approach to H control in delta domain
PublikacjaPraca dotyczy sterowania wielowymiarowym obiektem dynamicznym czasu ciągłego opisanym dyskretnoczasowym modelem w przestrzeni stanu, przy założeniu, że wskaźnik jakości sterowania oparty jest na normie H-inf. Odpowiednie zadanie optymalizacji tego wskaźnika rozwiązuje się, stosując tak zwaną względnie pierwszą J-bezstratną faktoryzację modelu sterowanego. Pokazano, że synteza optymalnego sterownika, wymagająca rozwiązania dwóch...
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Some remarks about numerical conditioning of discrete time Riccati eqations.
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I-lossless factorisations for robust H-inf-control in delta-domain
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Gradient based basis function algorithms for identification of quasi periodically varying processes.
PublikacjaW 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...
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Ku bezprzewodowym systemom czwartej generacji.
PublikacjaW pracy przedstawiono uwarunkowania, które wpłynęły na powstanie systemów radiokomunikacyjnych trzeciej generacji oraz spodziewany ich rozwój w najbliższych latach, którego celem jest zwiększenie szybkości i jakości transmisji danych, dostępnej dla użytkowników i w konsekwencji umożliwienie wprowadzania nowych usług oraz podnoszenie efektywności widmowej i pojemności tych systemów.
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Detekcja zakłóceń impulsowych w sygnałach fonicznych.
PublikacjaArtykuł poświęcony jest omówieniu problematyki związanej z wykrywaniem zakłóceń impulsowych występujących w sygnałach fonicznych. Proces detekcji zniekształconych próbek sygnału fonicznego jest etapem poprzedzającym ich rekonstrukcję. Polega ona na odtworzeniu nieznanych wartości próbek w oparciu o znane fragmenty sygnału. W pracy omówiono różne rodzaje zakłóceń impulsowych typowe dla archiwalnych i współczesnych sygnałów...
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Robust pole placement in delta domain for SISO plans
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Interakcyjne, zdalne laboratorium sterowania procesami przemysłowymi.
PublikacjaW pracy przedstawiono sposób realizacji wirtualnego laboratorium, w którym eksperymenty mogą być realizowane za pośrednictwem Internetu. Pokazano strukturę systemu umożliwiającego zdalną analizę pracy fizycznych obiektów oraz omówiono projekt stanowiska do badania układów sterowania ruchem odwróconego wahadła.
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Identyfikacja krytycznych uszkodzeń ścianek rurociągów na podstawie analizy MDCR w oparciu skaning ultradźwiękowy.
PublikacjaW pracy przedstawiono system ultradźwiękowych tłoków pomiarowych wysokiej rozdzielczości dostarczający informacji o parametrach geometrycznych wykrytych ubytków metalu w ściankach badanego rurociągu. Informacje te pozwalają na oszacowanie MDCR uznanego za jeden z podstawowych wskaźników pozwalających na bezpieczną eksploatację rurociągów.
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Wykorzystanie ultradźwiękowych tłoków pomiarowych do oceny uszkodzeń korozyjnych ścianek rurociągów magistralnych oraz wpływu ich na parametry eksploatacyjne.
PublikacjaW pracy przedstawione zostały zasady działania oraz parametry stosowanych w badaniach tłoków inteligentnych sposoby i metody przetwarzania danych pomiarowych, formy zobrazowania danych oraz postać tworzonych na podstawie inspekcji raportów przedkładanych operatorowi rurociągu. W drugiej części pracy przedstawione zostaną algorytmy umożliwiające wykorzystanie informacji o wykrytych na podstawie badania tłokiem inteligentnym ubytkach...
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Fast algorithms for identyfication of periodiccaly varying systems.
PublikacjaPraca 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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Niedoskonałości Moodle - ocena subiektywna
PublikacjaW pracy dokonano specyfikacji wymagań systemu zdalnego nauczania odpowiadającego charakterowi polskich uczelni. Skonfrontowano te wymagania z możliwościami i cechami bardzo popularnego, szczególnie w Polsce, systemu Moodle.
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Jednolita synteza diagnostycznych generatorów resztowych oparta na lewej strukturze własnej obserwatora.
PublikacjaW pracy prezentuje się jednolitą posadowioną geometrycznie metodę projektowania generatorów resztowych statycznie odprzęgniętych od zakłóceń, która prowadzi do sub-optymalnych rozwiązań problemu odpornego dopasowania ich struktury własnej, zakładającego realizację ustalonego zbioru wartości własnych. Odporność tego podejścia dotyczy dostatecznie dobrego uwarunkowania numerycznego projektowanej macierzy wektorów własnych.W pracy...
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Discrete-time predictive control design based on overparameterized delay-plant models and identified cancellation order.
PublikacjaPraca dotyczy uogólnionego sterowania predykcyjnego (GPC) obiektami opisanymi dyskretnoczasowymi modelami CARIMA z uproszczeniami (nieminimalnych, przeparametryzowanych) oraz o niezerowym opóźnieniu transportowym. Optymalne sterowanie predykcyjne wyznacza się na podstawie minimalnowariancyjnego oszacowania przyszłej odpowiedzi sterowanego obiektu. Poprzez analizę warunków rozwiązywalności zadania syntezy sterownika GPC, sformułowano...
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Multichannel self-optimizing active noise control scheme
PublikacjaThe problem of cancellation of a nonstationary sinusoidal interference, acting at the output of an unknown multivariable linear stable plant, is considered. The proposed cancellation scheme is a nontrivial extension of the SONIC (self-optimizing narrowband interference canceller) algorithm, developed earlier for single-input, single-output plants. In the important benchmark case - for disturbances with randomwalk-type amplitude...
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RENOVATION OF ARCHIVE AUDIO RECORDINGS USING SPARSE AUTOREGRESSIVE MODELING AND BIDIRECTIONAL PROCESSING
PublikacjaThe paper presents a new approach to elimination of broadband noise and impulsive disturbances from archive audio recordings. The proposed adaptive Kalman-like algorithm, based on a sparse autoregressive model of the audio signal, simultaneously detects noise pulses, interpolates the irrevocably distorted samples and performs signal smoothing. It is shown that bidirectional (forward-backward) processing of the archive signal improves...
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From the multiple frequency tracker to the multiple frequency smoother
PublikacjaThe 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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Localization of impulsive disturbances in archive audio signals using predictive matched filtering
PublikacjaThe problem of elimination of impulsive disturbances from archive audio signals is considered and its new solution, called predictive matched filtering, is proposed. The new approach is based on the observation that a large percentage of noise pulses corrupting archive audio recordings have highly repetitive shapes that match several typical “patterns”, called click templates. To localize noise pulses, click templates can be correlated...
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Genre-Based Music Language Modeling with Latent Hierarchical Pitman-Yor Process Allocation
PublikacjaIn this work we present a new Bayesian topic model: latent hierarchical Pitman-Yor process allocation (LHPYA), which uses hierarchical Pitman-Yor pr ocess priors for both word and topic distributions, and generalizes a few of the existing topic models, including the latent Dirichlet allocation (LDA), the bi- gram topic model and the hierarchical Pitman-Yor topic model. Using such priors allows for integration of -grams with a topic...
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Active feedback noise control in the presence of impulsive disturbances
PublikacjaThe 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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Multiple-channel frequency-adaptive active vibration control using SONIC
PublikacjaSONIC (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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Visualization of events using various kinds of synchronized data for the Border Guard
PublikacjaSTRADAR project is dedicated to streaming real-time data in a distributed dispatcher and teleinfor-mation system of the Border Guard. The Events Visualization Post is a software designed for simultaneous visualization of data of different types in BG headquarters. The software allows the operator to visualize files, images, SMS, SDS, video, audio, and current or archival data on naval situation on digital maps. All the visualized...
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Genre-Based Music Language Modeling with Latent Hierarchical Pitman-Yor Process Allocation
PublikacjaIn this work we present a new Bayesian topic model: latent hierarchical Pitman-Yor process allocation (LHPYA), which uses hierarchical Pitman-Yor pr ocess priors for both word and topic distributions, and generalizes a few of the existing topic models, including the latent Dirichlet allocation (LDA), the bi- gram topic model and the hierarchical Pitman-Yor topic model. Using such priors allows for integration of -grams with a topic model,...
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A self-optimization mechanism for generalized adaptive notch smoother
PublikacjaTracking 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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New results on estimation bandwidth adaptation
PublikacjaThe problem of identification of a nonstationary autoregressive signal using non-causal estimation schemes is considered. Noncausal estimators can be used in applications that are not time-critical, i.e., do not require real-time processing. A new adaptive estimation bandwidth selection rule based on evaluation of pseudoprediction errors is proposed, allowing one to adjust tracking characteristics of noncausal estimators to unknown...
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Adaptive Identification of Underwater Acoustic Channel with a Mix of Static and Time-Varying Parameters
PublikacjaWe 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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Identification of Fast Time-varying Communication Channels Using the Preestimation Technique
PublikacjaAccurate 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...
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Active Suppression of Nonstationary Narrowband Acoustic Disturbances
PublikacjaIn 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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Finite-window RLS algorithms
PublikacjaTwo 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...
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Fully Adaptive Savitzky-Golay Type Smoothers
PublikacjaThe 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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Robust algorithm for active feedback control of narrowband noise
PublikacjaThe 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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Radar time budget optimization subject to angle accuracy constraint via cognitive approach
PublikacjaThe 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...
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Sparse vector autoregressive modeling of audio signals and its application to the elimination of impulsive disturbances
PublikacjaArchive audio files are often corrupted by impulsive disturbances, such as clicks, pops and record scratches. This paper presents a new method for elimination of impulsive disturbances from stereo audio signals. The proposed approach is based on a sparse vector autoregressive signal model, made up of two components: one taking care of short-term signal correlations, and the other one taking care of long-term correlations. The method...
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe 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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Decoupled Kalman filter based identification of time-varying FIR systems
PublikacjaWhen 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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Generalized adaptive notch filters with frequency debiasing for tracking of polynomial phase systems
PublikacjaGeneralized 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...
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Frequency Guided Generalized Adaptive Notch Filtering - Tracking Analysis and Optimization
PublikacjaGeneralized 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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Parallel frequency tracking with built-in performance evaluation
PublikacjaThe 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...
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Capon-like DoA estimator for rotating arrays
PublikacjaWe 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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New semi-causal and noncausal techniques for detection of impulsive disturbances in multivariate signals with audio applications
PublikacjaThis paper deals with the problem of localization of impulsive disturbances in nonstationary multivariate signals. Both unidirectional and bidirectional (noncausal) detection schemes are proposed. It is shown that the strengthened pulse detection rule, which combines analysis of one-step-ahead signal prediction errors with critical evaluation of leave-one-out signal interpolation errors, allows one to noticeably improve detection results...
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Azimuth estimator for a rotating array radar with wide beam
PublikacjaThe 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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Pre-arrangement of solvability, complexity, stability and quality of GPC systems
PublikacjaPraca dotyczy podstawowych problemów strojenia algorytmów dyskretnoczasowego uogólnienia sterowania predykcyjnego (GPC). Optymalne sterowanie predykcyjne, w sensie pewnego kwadratowego funkcjonału kosztów, wyznacza się rozwiązując odpowiednie liniowe zadanie. W pracy podano warunki, przy których macierz tego zadania jest macierzą o pełnym kolumnowym rzędzie - co gwarantuje istnienie optymalnego sterownika. W następnej kolejności...
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Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublikacjaThe problem of identification of nonstationary stochastic processes (systems or signals) is considered and a new class of identification algorithms, combining the basis functions approach with local estimation technique, is described. Unlike the classical basis function estimation schemes, the proposed regularized local basis function estimators are not used to obtain interval approximations of the parameter trajectory, but provide...
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Multichannel self-optimizing narrowband interference canceller
PublikacjaThe 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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Localization of impulsive disturbances in audio signals using template matching
PublikacjaIn this paper, a new solution to the problem of elimination of impulsive disturbances from audio signals, based on the matched filtering technique, is proposed. The new approach stems from the observation that a large proportion of noise pulses corrupting audio recordings have highly repetitive shapes that match several typical “patterns”. In many cases a representative set of exemplary pulse waveforms can be extracted from the...
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Adaptive filtering approach to dynamic weighing: a checkweigher case study
PublikacjaDynamic 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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Central heating temperature control algorithm for systems with condensing boilers
PublikacjaThe problem of control of a central heating system in a small residence is considered. It is assumed that the system is based on a condensing boiler. Since the boiler efficiency depends on a returning water temperature, the proposed control goal is to provide proper air temperature in the residence as well as the lowest possible water temperature. The proposed algorithm is applied to two buildings. Both of them have the same heating...
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On tracking properties of real-valued generalized adaptive notch filters
PublikacjaGeneralized adaptive notch filters (GANFs) 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. The paper presents results of local performance analysis of a real-valued GANF algorithm, i.e., algorithm designed to track parameters of a real-valued system. This is an extension of the previous work which focused...
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On Bayesian Tracking and Prediction of Radar Cross Section
PublikacjaWe 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...
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Adaptive identification of sparse underwater acoustic channels with a mix of static and time-varying parameters
PublikacjaWe 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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ESTIMATION OF NONSTATIONARY HARMONIC SIGNALS AND ITS APPLICATION TO ACTIVE CONTROL OF MRI NOISE
PublikacjaA 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
PublikacjaThe 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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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe 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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Iterative learning approach to active noise control of highly autocorrelated signals with applications to machinery noise
PublikacjaThis 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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Analytical design of stable delta-domain generalized predictive control
PublikacjaPraca dotyczy analitycznej metody projektowania układów sterowania skalarnymi (SISO) obiektami czasu ciągłego według strategii uogólnionego sterowania predykcyjnego (GPC) w oparciu o dyskretnoczasowe modele takich obiektów. Założono wykorzystanie numeryczne odpornych modeli opartych o tak zwany operator delta. Przyjmując kwadratowy funkcjonał kosztów, w którym prognozowany przebieg przyszłego wyjścia sterowanego obiektu porównywany...
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Statistically efficient smoothing algorithm for time-varying frequency estimation
PublikacjaThe problem of extraction/elimination of a nonstationary sinusoidal signal 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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Detection of impulsive disturbances in archive audio signals
PublikacjaIn 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...
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Generalized adaptive notch smoothers for real-valued signals and systems
PublikacjaSystems 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...
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Robustified estimators of radar elevation angle using a specular multipath model
PublikacjaWe 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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On the lower smoothing bound in identification of time-varying systems
PublikacjaIn certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate in the identification process not only the currently available information, but also a number of ''future'' data points. The resulting estimation schemes, which involve smoothing, are not causal. Assuming that the infinite observation history is available, the paper...
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Fast clutter cancellation for noise radars via waveform design
PublikacjaCanceling 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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On DoA estimation for rotating arrays using stochastic maximum likelihood approach
PublikacjaThe 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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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublikacjaThe 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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On noncausal weighted least squares identification of nonstationary stochastic systems
PublikacjaIn this paper, we consider the problem of noncausal identification of nonstationary, linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted (windowed) least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts...
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Easy recipes for cooperative smoothing
PublikacjaIn 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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Self-Optimizing Adaptive Vibration Controller
PublikacjaThis paper presents a new approach to rejection of sinusoidal disturbances acting at the output of a discrete-time linear stable 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 proposed controller, called SONIC (self-optimizing narrowband interference canceller), combines the coefficient fixing technique,...
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Elimination of Impulsive Disturbances From Stereo Audio Recordings Using Vector Autoregressive Modeling and Variable-order Kalman Filtering
PublikacjaThis 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...
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Akaike's final prediction error criterion revisited
PublikacjaWhen 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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Generalized adaptive notch smoothing revisited
PublikacjaThe 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...
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Systemidentificationbasedapproachtodynamicweighing revisited
PublikacjaDynamicweighing,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.
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Generalized adaptive notch filter with a self-optimization capability
PublikacjaW 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.
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High-Precision FIR-Model-Based Dynamic Weighing System
PublikacjaConveyor 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...
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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublikacjaWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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Estimation and tracking of complex-valued quasi-periodically varying systems
PublikacjaW 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
PublikacjaW 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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New Algorithms for Adaptive Notch Smoothing
PublikacjaThe 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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Numerical conditioning of delta-domain Lyapunov and Riccati equations
PublikacjaW pracy rozważono problem uwarunkowania dyskretno czasowych równań Lapunowa oraz równań Riccatiego - to znaczy problem wrażliwości rozwiązań takich równań na odchyłki ich parametrów od nominalnych wartości. Zdefiniowano odpowiedni "różniczkowy" wskaźnik uwarunkowania oraz podano efektywną metodę szacowania jego wartości. Udowodniono teoretycznie - a także przekonująco zilustrowano na drodze numerycznej - twierdzenie głoszące, iż...
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Generalized Savitzky–Golay filters for identification of nonstationary systems
PublikacjaThe 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...
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Locally Adaptive Cooperative Kalman Smoothing and Its Application to Identification of Nonstationary Stochastic Systems
PublikacjaOne of the central problems of the stochastic approximation theory is the proper adjustment of the smoothing algorithm to the unknown, and possibly time-varying, rate and mode of variation of the estimated signals/parameters. In this paper we propose a novel locally adaptive parallel estimation scheme which can be used to solve the problem of fixed-interval Kalman smoothing in the presence of model uncertainty. The proposed solution...
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A new look at the statistical identification of nonstationary systems
PublikacjaThe 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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Application of regularized Savitzky–Golay filters to identification of time-varying systems
PublikacjaSavitzky–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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Identification of quasi-periodically varying systems using the combined nonparametric/parametric approach
PublikacjaW 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.
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Elimination of Impulsive Disturbances From Archive Audio Signals Using Bidirectional Processing
PublikacjaIn 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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Cheap Cancellation of Strong Echoes for Digital Passive and Noise Radars
PublikacjaThe 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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Melody Harmonization with Interpolated Probabilistic Models
PublikacjaMost melody harmonization systems use the generative hidden Markov model (HMM), which model the relation between the hidden chords and the observed melody. Relations to other variables, such as the tonality or the metric structure, are handled by training multiple HMMs or are ignored. In this paper, we propose a discriminative means of combining multiple probabilistic models of various musical variables by means of model interpolation....
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Dynamic mass measurement in checkweighers using a discrete time-variant low-pass filter
PublikacjaConveyor 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...