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    Wyświetlanie 1-9 z 9
    Tytuł:
    Inverse method for a one-stage spur gear diagnosis
    Autorzy:
    Akrout, A.
    Tounsi, D.
    Taktak, M.
    Abbes, M. S.
    Haddar, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/949292.pdf
    Data publikacji:
    2015
    Wydawca:
    Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
    Tematy:
    Independent Component Analysis (ICA)
    source identification
    gear mechanism
    geometrical defects
    Opis:
    In this paper, a source separation approach based on the Blind Source Separation (BSS) is presented. In fact, the Independent Component Analysis (ICA), which is the main technique of BSS, consists in extracting different source signals from several observed mixtures. This inverse method is very useful in many fields such as telecommunication, signal processing and biomedicine. It is also very attractive for diagnosis of mechanical systems such as rotating machines. Generally, dynamic responses of a given mechanical system (displacements, accelerations and speeds) measured through sensors are used as inputs for the identification of internal defaults. In this study, the ICA concept is applied to the diagnosis of a one-stage gear mechanism in which two types of defects (the eccentricity error and the localized tooth defect)are introduced. The finite element method allows determination of the signals corresponding to the acceleration in some locations of the system, and those signals may be used also in the ICA algorithm. Hence, the vibratory signatures of each defect can be identified by the ICA concept. Thus, a good agreement is obtained by comparing the expected default signatures to those achieved by the developed inverse method.
    Źródło:
    Journal of Theoretical and Applied Mechanics; 2015, 53, 3; 617-628
    1429-2955
    Pojawia się w:
    Journal of Theoretical and Applied Mechanics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Robustness study of the road profile estimation technique under uncertainty
    Autorzy:
    Ben Jdidia, Anoire
    Ben Hassen, Dorra
    Hentati, Taissir
    Abbes, Slim
    Haddar, Mohamed
    Powiązania:
    https://bibliotekanauki.pl/articles/2104771.pdf
    Data publikacji:
    2022
    Wydawca:
    Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
    Tematy:
    Independent Component Analysis (ICA) method
    Monte Carlo (MC) method
    road profile
    estimation
    Opis:
    This paper studies profile estimation a road. The prediction has been achieved using the Independent Component Analysis Method (ICA). The vehicle dynamic responses were cal- culated for different road profiles which were defined using an ISO norm. The robustness of this method was proven by implementing the stochastic Monte Carlo (MC) technique in the presence of inevitable uncertainty parameters simultaneously associated with the vehicle mass, spring stiffness and damping for different vehicle speeds and wind values. Convergence was assessed when comparing real profiles to simulated ones. The obtained results prove the efficiency of the ICA in estimating the profile variabilities under uncertainties.
    Źródło:
    Journal of Theoretical and Applied Mechanics; 2022, 60, 3; 521--533
    1429-2955
    Pojawia się w:
    Journal of Theoretical and Applied Mechanics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A comparison of algorithms for separation of synchronous subspaces
    Autorzy:
    Almeida, M.
    Bioucas-Dias, J.
    Vigário, R.
    Oja, E.
    Powiązania:
    https://bibliotekanauki.pl/articles/201566.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    phase locking
    synchrony
    source separation
    subspaces
    Independent Component Analysis (ICA)
    Independent Subspace Analysis (ISA)
    magnetoencephalogram (MEG)
    Opis:
    Independent Subspace Analysis (ISA) consists in separating sets (subspaces) of dependent sources, with different sets being independent of each other. While a few algorithms have been proposed to solve this problem, they are all completely general in the sense that they do not make any assumptions on the intra-subspace dependency. In this paper, we address the ISA problem in the specific context of Separation of Synchronous Sources (SSS), i.e., we aim to solve the ISA problem when the intra-subspace dependency is known to be perfect phase synchrony between all sources in that subspace. We compare multiple algorithmic solutions for this problem, by analyzing their performance on an MEG-like dataset.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 3; 455-460
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Impulse Noise Suppression Based on Power Iterative ICA in Power Line Communication
    Autorzy:
    Zhang, Wei
    Luo, Zhongqiang
    Xiong, Xingzhong
    Powiązania:
    https://bibliotekanauki.pl/articles/226439.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    power line communication(PLC)
    orthogonal frequency division multiplexing(OFDM) signal
    independent component analysis(ICA)
    impulse noise
    Opis:
    To overcome the detrimental influence of impulse noise in power line communication and the trap of scarce prior information in traditional noise suppression schemes , a power iteration based fast independent component analysis (PowerICA) based noise suppression scheme is designed in this paper. Firstly, the pseudo-observation signal is constructed by weighted processing so that single-channel blind separation model is transformed into the multi-channel observed model. Then the proposed blind separation algorithm is used to separate noise and source signals. Finally, the effectiveness of the proposed algorithm is verified by experiment simulation. Experiment results show that the proposed algorithm has better separation effect, more stable separation and less implementation time than that of FastICA algorithm, which also improves the real-time performance of communication signal processing.
    Źródło:
    International Journal of Electronics and Telecommunications; 2019, 65, 4; 651-656
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Feature vector or time-series – comparison of gestures representations in automatic gesture recognition systems
    Autorzy:
    Barczewska, K.
    Wójtowicz, W.
    Moszkowski, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/115720.pdf
    Data publikacji:
    2015
    Wydawca:
    Fundacja na Rzecz Młodych Naukowców
    Tematy:
    principal component analysis (PCA)
    independent component analysis (ICA)
    neural networks
    sign language
    automatic recognition
    analiza składowych głównych (PCA)
    analiza składowych niezależnych (ICA)
    sieci neuronowe
    język migowy
    automatyczne rozpoznawanie
    Opis:
    In this paper, we performed recognition of isolated sign language gestures - obtained from Australian Sign Language Database (AUSLAN) – using statistics to reduce dimensionality and neural networks to recognize patterns. We designated a set of 70 signal features to represent each gesture as a feature vector instead of a time series, used principal component analysis (PCA) and independent component analysis (ICA) to reduce dimensionality and indicate the features most relevant for gesture detection. To classify the vectors a feedforward neural network was used. The resulting accuracy of detection ranged between 61 to 87%.
    Źródło:
    Challenges of Modern Technology; 2015, 6, 1; 1-5
    2082-2863
    2353-4419
    Pojawia się w:
    Challenges of Modern Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Analysis of complex-valued functional magnetic resonance imaging data: are we just going through a "phase"?
    Autorzy:
    Calhoun, V.
    Adali, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/201555.pdf
    Data publikacji:
    2012
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    fMRI
    independent component analysis
    ICA
    phase
    complex-valued
    brain
    Opis:
    Functional magnetic resonance imaging (fMRI) data are acquired as a natively complex data set, however for various reasons the phase data is typically discarded. Over the past few years, interest in incorporating the phase information into the analyses has been growing and new methods for modeling and processing the data have been developed. In this paper, we provide an overview of approaches to understand the complex nature of fMRI data and to work with the utilizing the full information, both the magnitude and the phase. We discuss the challenges inherent in trying to utilize the phase data, and provide a selective review with emphasis on work in our group for developing biophysical models, preprocessing methods, and statistical analysis of the fully-complex data. Of special emphasis are the use of data-driven approaches, which are particularly useful as they enable us to identify interesting patterns in the complex-valued data without making strong assumptions about how these changes evolve over time, something which is challenging for magnitude data and even more so for the complex data. Finally, we provide our view of the current state of the art in this area and make suggestions for what is needed to make efficient use of the fully-complex fMRI data.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 3; 371-418
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Estimating independent components by mapping onto an orthogonal manifold
    Autorzy:
    Fiori, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/1933183.pdf
    Data publikacji:
    2008
    Wydawca:
    Politechnika Gdańska
    Tematy:
    independent component analysis
    ICA
    orthogonal group of matrices
    mappings onto manifolds
    Opis:
    Algorithms for independent component analysis (ICA) based on information-theoretic criteria optimization over differential manifolds have been devised over the last few years. The principles informing their design lead to various classes of learning rules, including the fixed-point and the geodesic-based ones. Such learning algorithms mainly differ by the way in which single learning steps are effected in the neural system's parameter space, i. e. by the action that a connection variable is moved by in the parameter space toward the optimal connection pattern. In the present paper, we introduce a new class of learning algorithms by recalling from the literature on differential geometry the concept of mapping onto manifolds, which provides a general way of acting upon a neural system's connection variable in order to optimize the learning criteria. The numerical behavior of the introduced learning algorithms is illustrated and compared with experiments carried out on mixtures of statistically-independent signals.
    Źródło:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2008, 12, 1-2; 105-120
    1428-6394
    Pojawia się w:
    TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Usuwanie artefaktów z danych EEG przy użyciu analizy składowych niezależnych
    Removal of artifacts from EEG data by means of Independent Component Analysis
    Autorzy:
    Górecka, J.
    Kaszyński, R.
    Powiązania:
    https://bibliotekanauki.pl/articles/158376.pdf
    Data publikacji:
    2008
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    ślepa separacja sygnałów
    analiza składowych niezależnych (ICA)
    sygnały EEG
    artefakt
    blind signal separation
    independent component analysis
    EEG data
    artifacts
    Opis:
    Celem przedstawionych wyników badań jest eliminacja wybranych niepożądanych sygnałów przy użyciu analizy składowych niezależnych. W artykule przedstawiono następujące algorytmy BSS (z ang. Blind Signal Separation): HJ oraz Infomax jako narzędzia do separacji i usuwania wybranej grupy artefaktów (mruganie powiek, artefakty mięśniowe) z przebiegów EEG. Jak udowodniono w eksperymentach proponowane algorytmy adaptacyjne mogą efektywnie wykrywać i usuwać wybrane artefakty z przebiegów EEG.
    The aim of the performed investigations is to remove selected undesired signals by means of ICA approach. In the paper there are presented the following algorithms BSS (Blind Signal Separation): HJ and Infomax for separation and removal of selected group of artifacts (eye blinks, muscle activity) from EEG recordings. It has been proved in the experiments which are described in the paper that the proposed adaptive algorithms can effectively detect and remove these selected artifacts from EEG recordings.
    Źródło:
    Pomiary Automatyka Kontrola; 2008, R. 54, nr 12, 12; 827-830
    0032-4140
    Pojawia się w:
    Pomiary Automatyka Kontrola
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Direct assessment of the fetal heart rate from abdominal composite recordings
    Autorzy:
    Moslem, B.
    Bazzi, O.
    Khalaf, J.
    Diab, M.O.
    Powiązania:
    https://bibliotekanauki.pl/articles/334031.pdf
    Data publikacji:
    2013
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    Fetal heart rate
    FHR
    Fetal Electrocardiogram
    FECG
    independent component analysis
    ICA
    adaptive filtering
    tętno płodu
    EKG płodu
    analiza składowych niezależnych
    filtrowanie adaptacyjne
    Opis:
    In respect to the main goal of our ongoing work for analyzing fetal electrocardiogram (FECG) signals for monitoring the health of the fetus, we investigate in this paper the possibility of extracting the fetal heart rate (FHR) directly from the abdominal composite recordings. Our proposed approach is based on a combination of Independent Component Analysis (ICA) and least mean square (LMS) adaptive filter. The FHR of the estimated FECG signal is finally compared to a reference value extracted from a FECG signal recorded by using a spiral electrode attached directly to the fetal scalp. The experimental results show that FHR can be successfully evaluated directly from the abdominal composite recordings without the need of using any external reference signal.
    Źródło:
    Journal of Medical Informatics & Technologies; 2013, 22; 143-149
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-9 z 9

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