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(Field of Science):
- automation, electronics, electrical engineering and space technologies (Engineering and Technology)
- biomedical engineering (Engineering and Technology)
- mechanical engineering (Engineering and Technology)
Ministry points: Help
| Year | Points | List |
|---|---|---|
| Year 2024 | 200 | Ministry scored journals list 2024 |
| Year | Points | List |
|---|---|---|
| 2024 | 200 | Ministry scored journals list 2024 |
| 2023 | 200 | Ministry Scored Journals List |
| 2022 | 200 | Ministry Scored Journals List 2019-2022 |
| 2021 | 200 | Ministry Scored Journals List 2019-2022 |
| 2020 | 200 | Ministry Scored Journals List 2019-2022 |
| 2019 | 200 | Ministry Scored Journals List 2019-2022 |
| 2018 | 45 | A |
| 2017 | 45 | A |
| 2016 | 45 | A |
| 2015 | 45 | A |
| 2014 | 45 | A |
| 2013 | 45 | A |
| 2012 | 40 | A |
| 2011 | 40 | A |
| 2010 | 32 | A |
Model:
Points CiteScore:
| Year | Points |
|---|---|
| Year 2023 | 10.7 |
| Year | Points |
|---|---|
| 2023 | 10.7 |
| 2022 | 10.7 |
| 2021 | 11.2 |
| 2020 | 11.8 |
| 2019 | 12.4 |
| 2018 | 12 |
| 2017 | 10.9 |
| 2016 | 10.6 |
| 2015 | 8.7 |
| 2014 | 8.3 |
| 2013 | 8 |
| 2012 | 9.2 |
| 2011 | 7.6 |
Impact Factor:
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Papers published in journal
Filters
total: 13
Catalog Journals
Year 2021
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Application of regularized Savitzky–Golay filters to identification of time-varying systems
PublicationSavitzky–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....
Year 2020
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A new look at the statistical identification of nonstationary systems
PublicationThe 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...
Year 2019
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Generalized Savitzky–Golay filters for identification of nonstationary systems
PublicationThe 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...
Year 2017
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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublicationWhen 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...
Year 2013
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Generalized adaptive comb filters/smoothers and their application to the identification of quasi-periodically varying systems and signals
PublicationThe 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...
Year 2011
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On noncausal weighted least squares identification of nonstationary stochastic systems
PublicationIn 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...
Year 2010
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Easy recipes for cooperative smoothing
PublicationIn 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...
Year 2009
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Self-optimizing generalized adaptive notch filters - comparison of three optimization strategies
PublicationThe 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...
Year 2008
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On ''cheap smoothing'' opportunities in identification of time-varying systems
PublicationIn 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
PublicationIn 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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Optimal and suboptimal algorithms for identification of time-varying systems with randomly drifting parameters
PublicationNoncausal 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...
Year 2007
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Generalized adaptive notch filters with frequency debiasing for tracking of polynomial phase systems
PublicationGeneralized 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...
Year 2002
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A J-lossless coprime factorisation approach to H control in delta domain
PublicationPraca 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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