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Katedra Systemów Automatyki
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wszystkich: 196
Katalog Publikacji
Rok 2023
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Active Control of Highly Autocorrelated Machinery Noise in Multivariate Nonminimum Phase Systems
PublikacjaIn this paper, a novel multivariate active noise control scheme, designed to attenuate disturbances with high autocorrelation characteristics and preserve background signals, is proposed. The algorithm belongs to the class of feedback controllers and, unlike the popular feedforward FX-LMS approach, does not require availability of a reference signal. The proposed approach draws its inspiration from the iterative learning control...
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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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Towards Robust Identification of Nonstationary Systems
PublikacjaThe article proposes a fast, two-stage method for the identification of nonstationary systems. The method uses iterative reweighting to robustify the identification process against the outliers in the measurement noise and against the numerical errors that may occur at the first stage of identification. We also propose an adaptive algorithm to optimize the values of the hyperparameters that are crucial for this new method.
Rok 2022
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A Control Theoretical Approach to Spectral Factorization is Unstable
PublikacjaLocal stability analysis of a recently proposed recursive feedback-based approach to spectral factorization is performed. The method is found not to give stability guarantees. Interestingly enough, its global behavior often allows one to obtain reasonable approximations of spectral factorizations if a suitable stopping criterion is employed.
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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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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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Estymacja współrzędnych kątowych w radarze trójwspółrzędnym z elektronicznym skanowaniem wiązki i obracaną anteną planarną
PublikacjaW rozprawie zawarto historię radiolokacji oraz sposób obróbki sygnałów i danych radarowych przed etapem estymacji. Przedstawiono oraz przetestowano klasyczne metody estymacji współrzędnych wraz ze wskazaniem ich słabych oraz mocnych stron. Zaproponowano uodpornione warianty estymatorów największej wiarygodności, które pozwolił poprawić jakość oszacowania przy estymacji elewacji w warunkach propagacji wielodrogowej, redukując jednocześnie...
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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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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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Stardust - Investigation of Microbes in the Stratosphere
PublikacjaThe stratospheric microbiome has been investigated several times using the methods of classical microbiology. In this experiment, we have combined them with some novel approaches including whole- metagenome amplification, Maldi TOF mass spectrometry and Sanger DNA sequencing. The results of the experiment may provide the scientists with knowledge about the mechanisms of survivability of microorganisms in stratospheric conditions...
Rok 2021
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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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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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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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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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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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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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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...
Rok 2020
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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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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...