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Wyniki wyszukiwania dla: identification of time-varying systems
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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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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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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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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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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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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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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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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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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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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 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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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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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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Fast recursive basis function estimators for identification of time-varying processes
PublikacjaW pracy wprowadzono nową kategorię filtrów adaptacyjnych opartych na metodzie funkcji bazowych i wykorzystujących koncepcję postfiltracji. Proponowane algorytmy pozwalają połączyć niską złożoność obliczeniową i dobre właściwości śledzące.
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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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ADAPTIVE IDENTIFICATION OF TIME-VARYING IMPULSE RESPONSE OF UNDERWATER ACOUSTIC COMMUNICATION CHANNEL
PublikacjaThe transmission properties of underwater acoustic communication channel can change dynamically due to the movement of acoustic system transmitter and receiver or underwater objects reflecting transmitted signal. The time-varying impulse response measurement and estimation are necessary to match the physical layer of data transmission to instantaneous channel propagation conditions. Using the correlative measurement method, impulse...
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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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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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Designing optimal and safe control strategies for time-varying dynamical systems
PublikacjaPublikacja opisuje metodę projektowania optymalnej trajektorii punktu pracy w czasoprzestrzeni stanów przy wykorzystaniu algorytmów optymalizacji grafowej. Zakłada się deterministyczny charakter zmian dynamiki rozpatrywanego procesu. Przestrzeń robocza, będąca ograniczonym podzbiorem czasoprzestrzeni stanów, jest dzielona na zbiór segmentów, którym przypisywane są wielkości reprezentujące właściwości dynamiki własnej w obrębie...
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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.