ISSN:
eISSN:
Disciplines
(Field of Science):
- automation, electronics, electrical engineering and space technologies (Engineering and Technology)
- information and communication technology (Engineering and Technology)
- biomedical engineering (Engineering and Technology)
- civil engineering, geodesy and transport (Engineering and Technology)
- mechanical engineering (Engineering and Technology)
- computer and information sciences (Natural sciences)
(Field of Science)
Ministry points: Help
Year | Points | List |
---|---|---|
Year 2024 | 140 | Ministry scored journals list 2024 |
Year | Points | List |
---|---|---|
2024 | 140 | Ministry scored journals list 2024 |
2023 | 140 | Ministry Scored Journals List |
2022 | 140 | Ministry Scored Journals List 2019-2022 |
2021 | 140 | Ministry Scored Journals List 2019-2022 |
2020 | 140 | Ministry Scored Journals List 2019-2022 |
2019 | 140 | Ministry Scored Journals List 2019-2022 |
2018 | 40 | A |
2017 | 40 | A |
2016 | 40 | A |
2015 | 40 | A |
2014 | 40 | A |
2013 | 40 | A |
2012 | 40 | A |
2011 | 40 | A |
2010 | 32 | A |
Model:
Points CiteScore:
Year | Points |
---|---|
Year 2023 | 11.2 |
Year | Points |
---|---|
2023 | 11.2 |
2022 | 10.1 |
2021 | 10.5 |
2020 | 11.5 |
2019 | 11.2 |
2018 | 9.8 |
2017 | 9.4 |
2016 | 8.7 |
2015 | 8 |
2014 | 8.1 |
2013 | 8.1 |
2012 | 7.2 |
2011 | 6.5 |
Impact Factor:
Sherpa Romeo:
Papers published in journal
Filters
total: 18
Catalog Journals
Year 2024
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On optimal tracking of rapidly varying telecommunication channels
PublicationWhen parameters of mobile telecommunication channels change rapidly, classical adaptive filters, such as exponentially weighted least squares algorithms or gradient algorithms, fail to estimate them with sufficient accuracy. In cases like this, one can use identification methods based on explicit models of parameter changes such as the method of basis functions (BF). When prior knowledge about parameter changes is available the...
Year 2021
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Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublicationThe 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...
Year 2020
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On DoA estimation for rotating arrays using stochastic maximum likelihood approach
PublicationThe flexibility needed to construct DoA estimators that can be used with rotating arrays subject to rapid variations of the signal frequency is offered by the stochastic maximum likelihood approach. Using a combination of analytic methods and Monte Carlo simulations, we show that for low and moderate source correlations the stochastic maximum likelihood estimator that assumes noncorrelated sources has accuracy comparable to the...
Year 2019
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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublicationThe problem of identification of nonstationary multivariate autoregressive processes using noncausal local estimation schemes is considered and a new approach to joint selection of the model order and the estimation bandwidth is proposed. The new selection rule, based on evaluation of pseudoprediction errors, is compared with the previously proposed one, based on the modified Akaike’s final prediction error criterion.
Year 2017
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New semi-causal and noncausal techniques for detection of impulsive disturbances in multivariate signals with audio applications
PublicationThis paper deals with the problem of localization of impulsive disturbances in nonstationary multivariate signals. Both unidirectional and bidirectional (noncausal) detection schemes are proposed. It is shown that the strengthened pulse detection rule, which combines analysis of one-step-ahead signal prediction errors with critical evaluation of leave-one-out signal interpolation errors, allows one to noticeably improve detection results...
Year 2015
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Frequency Guided Generalized Adaptive Notch Filtering - Tracking Analysis and Optimization
PublicationGeneralized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems, encountered e.g., in RF applications when Doppler effect takes place. Current state of the art GANFs can deliver highly accurate estimates of system variations’ frequency, but underperform in terms of accuracy of system coefficient estimates. The paper proposes a novel multistage GANF with improved coefficient...
Year 2012
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Cheap Cancellation of Strong Echoes for Digital Passive and Noise Radars
PublicationThe problem of cancellation of strong, potentially nonstationary,echoes in noise radars and passive radars utilizing digitaltransmissions is considered. The proposed solution is a multi-stage procedure.Initial clutter estimates, obtained using the least mean squares(LMS) algorithm, are refined using specially designed filters, "matched"to spectral densities of targets and clutter. When the postprocessing filtersare noncausal, the...
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Locally Adaptive Cooperative Kalman Smoothing and Its Application to Identification of Nonstationary Stochastic Systems
PublicationOne of the central problems of the stochastic approximation theory is the proper adjustment of the smoothing algorithm to the unknown, and possibly time-varying, rate and mode of variation of the estimated signals/parameters. In this paper we propose a novel locally adaptive parallel estimation scheme which can be used to solve the problem of fixed-interval Kalman smoothing in the presence of model uncertainty. The proposed solution...
Year 2011
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New Algorithms for Adaptive Notch Smoothing
PublicationThe problem of extraction/elimination of a nonstationary complex sinusoidal signal buried in noise is considered. This problem is usually solved using adaptive notch filtering (ANF)algorithms. It is shown that accuracy of signal estimation can be increased if the results obtained from ANF are further processed using a cascade of appropriately designed filters. The resulting adaptive notch smoothing (ANS) algorithms can be employed...
Year 2010
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Generalized adaptive notch smoothing revisited
PublicationThe problem of identification of quasi-periodically varying dynamic systems is considered. This problem can be solved using generalized adaptive notch filtering (GANF) algorithms. It is shown that the accuracy of parameter estimates can be significantly increased if the results obtained from GANF are further processed using a cascade of appropriately designed filters. The resulting generalized adaptive notch smoothing (GANS) algorithm...
Year 2008
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Generalized adaptive notch smoothers for real-valued signals and systems
PublicationSystems with quasi-periodically varying coefficients can be tracked using the algorithms known as generalized adaptive notch filters (GANFs). GANF algorithms can be considered an extension, to the system case, of classical adaptive notch filters (ANFs). We show that estimation accuracy of the existing algorithms, as well as their robustness to the choice of design parameters, can be considerably improved by means of compensating...
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Statistically efficient smoothing algorithm for time-varying frequency estimation
PublicationThe problem of extraction/elimination of a nonstationary sinusoidal signal from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF) algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS) algorithm...
Year 2007
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On tracking properties of real-valued generalized adaptive notch filters
PublicationGeneralized adaptive notch filters (GANFs) 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. The paper presents results of local performance analysis of a real-valued GANF algorithm, i.e., algorithm designed to track parameters of a real-valued system. This is an extension of the previous work which focused...
Year 2006
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Generalized adaptive notch filter with a self-optimization capability
PublicationW pracy przedstawiono samonastrajalny wariant tzw. uogólnionego adaptacyjnego filtru wycinającego. Automatycznym strojeniem objęte są dwa współczynniki wzmocnienia adaptacji, odpowiedzialne za śledzenie amplitud i częstotliwości parametrów identyfikowanego obiektu.
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Tracking analysis of a generalized adaptive notch filter
PublicationUogólniony adaptacyjny filtr wycinający służy do identyfikacji obiektów zmieniających się w sposób pseudookresowy. W pracy przedstawiono analizę własności śledzących takiego filtru a także omówiono zasady jego strojenia.
Year 2003
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Fast algorithms for identyfication of periodiccaly varying systems.
PublicationPraca dotyczy identyfikacji obiektów o parametrach zmieniających się w sposób okresowy. Zaproponowane algorytmy śledzenia parametrów cechują się niską złożonością obliczeniową, typową dla podejścia gradientowego a zarazem wysoką jakością śledzenia typową dla złożonych algorytmów opartych na metodzie funkcji bazowych.
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Synthesis and biological evaluation of 2,7-Dihydro-3H-dibenzo[de,h]cinnoli- ne-3,7-done derivatives a novel group of anticancer agents active on a multidrug resistance cell line.
PublicationZsyntezowano serię pochodnych pirydazonu z jednym lub dwoma łańcuchami bocznymi w różnych pozycjach chromoforu tetracyklicznego. Związki wykazały aktywność cytoksyczną na mysią białaczkę L1210 i ludzką k562 oraz na linii komórkowej oporności krzyżowej MDR (k562/DX). Dwa najbardziej aktywne związki przetestowano in vivo na mysiej białaczce P388. Wykazały one aktywność przeciwnowotworową porównywalną z aktywnością Mitoxantronu.
Year 2002
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Fast recursive basis function estimators for identification of time-varying processes
PublicationW 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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