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AUTOMATICA

ISSN:

0005-1098

eISSN:

1873-2836

Disciplines
(Field of Science):

  • Automation, electronic and electrical engineering (Engineering and Technology)
  • Biomedical engineering (Engineering and Technology)
  • Mechanical engineering (Engineering and Technology)

Ministry points: Help

Ministry points - current year
Year Points List
Year 2021 200 Ministry Scored Journals List 2019
Ministry points - previous years
Year Points List
2021 200 Ministry Scored Journals List 2019
2020 200 Ministry Scored Journals List 2019
2019 200 Ministry Scored Journals List 2019
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
2009 32 A
2008 32 A

Model:

Hybrid

Points CiteScore:

Points CiteScore - current year
Year Points
Year 2020 11.8
Points CiteScore - previous years
Year Points
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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total: 13

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Catalog Journals

Year 2021
Year 2020
  • A new look at the statistical identification of nonstationary systems
    Publication

    The 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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Year 2019
  • Generalized Savitzky–Golay filters for identification of nonstationary systems
    Publication

    The 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...

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Year 2017
  • On adaptive covariance and spectrum estimation of locally stationary multivariate processes
    Publication

    - AUTOMATICA - Year 2017

    When 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...

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Year 2013
Year 2011
  • On noncausal weighted least squares identification of nonstationary stochastic systems
    Publication

    - AUTOMATICA - Year 2011

    In 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...

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Year 2010
  • Easy recipes for cooperative smoothing
    Publication

    - AUTOMATICA - Year 2010

    In 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...

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Year 2009
Year 2008
  • On ''cheap smoothing'' opportunities in identification of time-varying systems
    Publication

    - AUTOMATICA - Year 2008

    In 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
    Publication

    - AUTOMATICA - Year 2008

    In 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
    Publication

    - AUTOMATICA - Year 2008

    Noncausal 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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Year 2007
Year 2002
  • A J-lossless coprime factorisation approach to H control in delta domain
    Publication

    - AUTOMATICA - Year 2002

    Praca 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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