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Wyniki wyszukiwania dla: TIME-VARYING SYSTEM
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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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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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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 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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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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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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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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Linear Time-Varying Dynamic-Algebraic Equations of Index One on Time Scales
PublikacjaIn this paper, we introduce a class of linear time-varying dynamic-algebraic equations (LTVDAE) of tractability index one on ar- bitrary time scales. We propose a procedure for the decoupling of the considered class LTVDAE. Explicit formulae are written down both for transfer operator and the obtained decoupled system. A projector ap- proach is used to prove the main statement of the paper and sufficient conditions of decoupling...