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Wyświetlanie 1-2 z 2
Tytuł:
A Fast Method of Feature Extraction for Lowering Vehicle Pass-By Noise Based on Nonnegative Tucker3 Decomposition
Autorzy:
Wang, H.
Cheng, G.
Deng, G.
Li, X.
Li, H.
Huang, Y.
Powiązania:
https://bibliotekanauki.pl/articles/177883.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
vehicle pass-by noise
NTD
feature extraction
sound pressure level
Opis:
Usually, the judgement of one type fault of vehicle pass-by noise is difficult for engineers, especially when some significant features are disturbed by other interference noise, such as the squealing noise is almost simultaneous with the whistle in the exhaust system. In order to cope with this problem, a new method, with the antinoise ability of the algorithm on the condition by which the features are entangled, is developed to extract clear features for the fault analysis. In the proposed method, the nonnegative Tucker3 decomposition (NTD) with fast updating algorithm, signed as NTD_FUP, can find out the natural frequency of the parts/components from the exhaust system. Not only does the NTD_FUP extract clear features from the confused noise, but also it is superior to the traditional methods in practice. Then, an aluminium-foil alloy material, which is used for the heat shield for its lower noise radiation, replaces the aluminium alloy alone. Extensive experiments show that the sound pressure level of the vehicle pass-by noise is reduced 0.9 dB(A) by the improved heat shield, which is also considered as a more lightweight design for the exhaust system of an automobile.
Źródło:
Archives of Acoustics; 2017, 42, 4; 619-629
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fast and unique Tucker decompositions via multiway blind source separation
Autorzy:
Zhou, G.
Cichocki, A.
Powiązania:
https://bibliotekanauki.pl/articles/201572.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Multiway Blind Source Separation (MBSS)
Multilinear Independent Component Analysis (MICA)
Constrained tensor decompositions
Tucker models
Nonnegative Tucker Decomposition (NTD)
Opis:
A multiway blind source separation (MBSS) method is developed to decompose large-scale tensor (multiway array) data. Benefitting from all kinds of well-established constrained low-rank matrix factorization methods, MBSS is quite flexible and able to extract unique and interpretable components with physical meaning. The multilinear structure of Tucker and the essential uniqueness of BSS methods allow MBSS to estimate each component matrix separately from an unfolding matrix in each mode. Consequently, alternating least squares (ALS) iterations, which are considered as the workhorse for tensor decompositions, can be avoided and various robust and efficient dimensionality reduction methods can be easily incorporated to pre-process the data, which makes MBSS extremely fast, especially for large-scale problems. Identification and uniqueness conditions are also discussed. Two practical issues dimensionality reduction and estimation of number of components are also addressed based on sparse and random fibers sampling. Extensive simulations confirmed the validity, flexibility, and high efficiency of the proposed method. We also demonstrated by simulations that the MBSS approach can successfully extract desired components while most existing algorithms may fail for ill-conditioned and large-scale problems.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 3; 389-405
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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