prof. dr hab. inż. Maciej Niedźwiecki
Zatrudnienie
- Profesor w Katedra Sygnałów i Systemów WETI
Publikacje
Filtry
wszystkich: 108
Katalog Publikacji
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Zastosowanie filtracji cząsteczkowej w systemie nawigacji dla niewidomych
PublikacjaW pracy opisano system nawigacji dla niewidomych wyposażony w odbiornik GPS, mapę cyfrową i czujniki nawigacji zliczeniowej. Problem estymacji położenia pieszego w oparciu o informacje z różnych źródeł rozwiązano przy użyciu podejścia zwanego filtracją cząsteczkową. Zastosowano techniki grupowania cząsteczek i odwzorowania w obszar wypukły, aby zagwarantować, że oszacowania położenia w każdej chwili spełniają ograniczenia nakładane...
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Interfejs urządzenia wykrywającego i odczytującego napisy dla osoby niewidomej
PublikacjaZadaniem projektowanego urządzenia wykrywającego i odczytującego napisy jest umożliwienie niewidomemu samodzielnego rozpoznawania treści napisów i w konsekwencji wyboru właściwego tramwaju, sklepu, ulicy czy pokoju w urzędzie. Urządzenia takiego nie można sobie oczywiście wyobrazić bez zastosowania nowoczesnych metod przetwarzania i rozpoznawania obrazów. Najlepsze jednak metody nie dadzą oczekiwanych rezultatów, o ile urządzenie...
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Fast Algorithms for Identification of Time-Varying Systems with Both Smooth and Discontinuous Parameter Changes
PublikacjaThe 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.
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Regularized identification of fast time-varying systems - comparison of two regularization strategies
PublikacjaThe problem of identification of a time-varying FIR system is considered and solved using the local basis function approach. It is shown that the estimation (tracking) results can be improved by means of regularization. Two variants of regularization are proposed and compared: the classical L2 (ridge) regularization and a new, reweighted L2 one. It is shown that the new approach can outperform the classical one and 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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Optimally regularized local basis function approach to identification of time-varying systems
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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Karhunen-Loeve-based approach to tracking of rapidly fading wireless communication channels
PublikacjaWhen parameters of wireless communication channels vary at a fast rate, simple estimation algorithms, such as weighted least squares (WLS) or least mean squares (LMS) algorithms, cannot estimate them with the accuracy needed to secure the reliable operation of the underlying communication systems. In cases like this, the local basis function (LBF) estimation technique can be used instead, significantly increasing the achievable...
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On bidirectional preestimates and their application to identification of fast time-varying systems
PublikacjaWhen applied to the identification of time-varying systems, such as rapidly fading telecommunication channels, adaptive estimation algorithms built on the local basis function (LBF) principle yield excellent tracking performance but are computationally demanding. The subsequently proposed fast LBF (fLBF) algorithms, based on the preestimation principle, allow a substantial reduction in complexity without significant performance...
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An improved frequency estimator for an adaptive active noise control scheme
PublikacjaAn 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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Medley filters - simple tools for efficient signal smoothing
PublikacjaMedley filters are defined as convex combinations of elementary smoothing filters (averaging, median) with different smoothing bandwidths. It is shown that when adaptive weights of such a mixture are evaluated using the recently proposed Bayesian rules, one obtains a tool which often outperforms the state-of-the-art wavelet-based smoothing algorithms. Additionally, unlike wavelet-based procedures, medley filters can easily cope...
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Multifrequency self-optimizing narrowband interference canceller
PublikacjaThe problem of cancellation of a nonstationary sinusoidal interference, acting at the output of a linear stable plant, is considered. It is assumed that disturbance is a multifrequency narrowband signal, and that system output is contaminated with wideband noise. It is not assumed that the reference signal is available. Two disturbance cancelling schemes are proposed, one for disturbances with unrelated frequency components, and...
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Locally-adaptive Kalman smoothing approach to identification of nonstationary stochastic systems
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Elimination of clicks from archive speech signals using sparse autoregressive modeling
PublikacjaThis 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...
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Identification of quasi-periodically varying systems with quasi-linear frequency changes
PublikacjaThe 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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Self-optimizing narrowband interference canceller - can reference signal help?
PublikacjaSONIC (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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On the instantaneous frequency smoothing for signals with quasi-linear frequency changes
PublikacjaThe 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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Semi-adaptive feedback active control of MRI noise
PublikacjaA 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.
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On cooperative image denoising
PublikacjaIn this paper we suggest how several competing image denoising algorithms, differing in design parameters, or even in design principles, can be combined together to yield a better and more reliable denoising algorithm. The proposed fusion mechanism allows one to combine practically all kinds of noise reduction tools. It also allows one to account for the distribution of measurement noise, and in particular - to cope with heavy-tailed...
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On noncausal 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 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 its smoothing...
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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]
PublikacjaThe 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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Automated detection of sleep apnea and hypopnea events based on robust airflow envelope tracking
PublikacjaThe 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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Elimination of impulsive disturbances from stereo audio recordings
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. 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...
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Elimination of impulsive disturbances from archive audio files – comparison of three noise pulse detection schemes
PublikacjaThe 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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Usuwanie odblasków linii laserowej
PublikacjaW nowoczesnych zrobotyzowanych systemach produkcyjnych coraz częściej stosuje się różnego rodzaju czujniki montowane na ramieniu robota, umożliwiające automatyczne rozpoznawanie położenia i kształtu obiektów znajdujących się w polu roboczym. Pozwala to na adaptacyjne dostosowywanie procesu technologicznego do zaistniałej sytuacji. Wyposażając robota w kamerę oraz linijkę laserową możliwe jest stworzenie zrobotyzowanego skanera...
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SONIC - Self-optimizing narrowband interference canceler: comparison of two frequency tracking strategies
PublikacjaThis paper presents a new approach to rejection of complex-valued sinusoidal disturbances acting at the output of a discrete-time linear stable plant with unknown and possibly time-varying 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. The proposed disturbance...
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System lokalizacji dla osób niewidomych
PublikacjaPrzedstawiono prototyp systemu lokalizacji łączący nawigację satelitarną z nawigacją zliczeniową, który informuje niewidomego użytkownika o aktualnym położeniu oraz opisuje najbliższe otoczenie na podstawie interaktywnego planu miasta. W systemie zastosowano opracowane algorytmy wyznaczania pozycji wykorzystujące filtrację Kalmana lub filtrację cząsteczkową, co pozwoliło znacznie zmniejszyć błędy oszacowań położenia.
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A simple way of increasing estimation accuracy of generalized adaptive notch filters
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. 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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Optimal and suboptimal algorithms for identification of time-varying systems with randomly drifting parameters
PublikacjaNoncausal estimation algorithms, which involve smoothing, can be used for off-line identification of nonstationary systems. Since smoothingis based on both past and future data, it offers increased accuracy compared to causal (tracking) estimation schemes, incorporating past data only. It is shown that efficient smoothing variants of the popular exponentially weighted least squares and Kalman filter-based parameter trackers can...
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On ''cheap smoothing'' opportunities 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 into 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. Despite the possible performance improvements, the existing smoothing...
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Variable-structure algorithm for identification of quasi-periodically varying systems
PublikacjaThe paper presents a variable-structure version of a generalized notchfiltering (GANF) algorithm. Generalized notch filters are used for identification of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. The proposed algorithm is a cascade of two GANF filters: a multiple-frequency "precise" filter bank, used for precise system tracking, and a...
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Self-optimizing generalized adaptive notch filters - comparison of three optimization strategies
PublikacjaThe paper provides comparison of three different approaches to on-line tuning of generalized adaptive notch filters (GANFs) the algorithms used for identification/tracking of quasi-periodically varying dynamic systems. Tuning is needed to adjust adaptation gains, which control tracking performance of ANF algorithms, to the unknown and/or time time-varying rate of system nonstationarity. Two out ofthree compared approaches are classical...
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A new approach to active noise and vibration control - [Part I: the known frequency case]
PublikacjaThis 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]
PublikacjaThis 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...
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Local basis function estimators for identification of nonstationary systems
PublikacjaThe problem of identification of a nonstationary stochastic system is considered and solved using local basis function approximation of system parameter trajectories. Unlike the classical basis function approach, which yields parameter estimates in the entire analysis interval, the proposed new identification procedure is operated in a sliding window mode and provides a sequence of point (rather than interval) estimates. It is...
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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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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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On Adaptive Spectrum Estimation of Multivariate Autoregressive Locally Stationary Processes
PublikacjaAutoregressive 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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Fast Basis Function Estimators for Identification of Nonstationary Stochastic Processes
PublikacjaThe 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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Tracking analysis of a generalized adaptive notch filter
PublikacjaUogólniony adaptacyjny filtr wycinający służy do identyfikacji obiektów zmieniających się w sposób pseudookresowy. W pracy przedstawiono analizę własności śledzących takiego filtru a także omówiono zasady jego strojenia.
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Multiple frequency tracker with improved tracking Capabilities
PublikacjaW pracy zaproponowano prostą modyfikację znanego z literatury wieloczęstotliwościowego adaptacyjnego filtra wycinającego, prowadzącą do istotnej poprawy jego charakterystyk nadążania.
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New Approach to Noncasual Identification of Nonstationary Stochastic FIR Systems Subject to Both Smooth and Abrupt Parameter Changes
PublikacjaIn this technical note, we consider the problem of finite-interval parameter smoothing for a class of nonstationary linear stochastic systems subject to both smooth and abrupt parameter changes. The proposed parallel estimation scheme combines the estimates yielded by several exponentially weighted basis function algorithms. The resulting smoother automatically adjusts its smoothing bandwidth to the type and rate of nonstationarity...
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BUILT IN PERFORMANCE EVALUATION FOR AN ADAPTIVE NOTCH FILTER
PublikacjaThe 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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Hybrid SONIC: joint feedforward–feedback narrowband interference canceler
PublikacjaSONIC (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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On autoregressive spectrum estimation using the model averaging technique
PublikacjaThe 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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Two-Stage Identification of Locally Stationary Autoregressive Processes and its Application to the Parametric Spectrum Estimation
PublikacjaThe problem of identification of a nonstationary autoregressive process with unknown, and possibly time-varying, rate of parameter changes, is considered and solved using the parallel estimation approach. The proposed two-stage estimation scheme, which combines the local estimation approach with the basis function one, offers both quantitative and qualitative improvements compared with the currently used single-stage methods.
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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 joint order and bandwidth selection for identification of nonstationary autoregressive processes
PublikacjaWhen identifying a nonstationary autoregressive process, e.g. for the purpose of signal prediction or parametric spectrum estimation, two important decisions must be taken. First, one should choose the appropriate order of the autoregressive model, i.e., the number of autoregressive coefficients that will be estimated. Second, if identification is carried out using the local estimation technique, such as the localized version of...
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On adaptive selection of estimation bandwidth for analysis of locally stationary multivariate processes
PublikacjaWhen estimating the correlation/spectral structure of a locally stationary process, one should choose the so-called estimation bandwidth, related to the effective width of the local analysis window. The choice should comply with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive estimation variance. The paper presents a novel method...
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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.
PublikacjaArtykuł 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.
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