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Wyszukujesz frazę "Leng, J" wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
Piezoelectric effect on thermoelastic Lamb waves in functionally graded plates
Autorzy:
Wang, X.
Ren, X.
Yu, J.
Zhou, H.
Zhang, X.
Leng, J
Powiązania:
https://bibliotekanauki.pl/articles/38695708.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
thermoelastic wave
attenuation
FGM
piezoelectric effect
physical field distributions
Opis:
Based on the Lord–Shulman thermoelectric elasticity theory, the piezoelectric effect on the thermoelastic Lamb wave propagation in the functionally graded material (FGM) plate is investigated. The coupled wave equations are solved by employing the Legendre polynomial series approach (LSPA), which poses the advantages of small scale of eigenvalues matrix and a convenient solution. It can directly obtain the complex wave number solutions without iteration. The obtained complex solutions, which represent the wave propagation and attenuation, are compared with those available data. Numerical examples show that the influence of gradient is profound. Results indicate that the piezoelectric effects on attenuation with the open and closed circuit condition are consistent for the S0 and S1 modes, but are inconsistent for the A0 and A1 modes. Although the piezoelectric effect is weak on the dispersion and attenuation of thermal waves, it is notable for their physical field distributions. In addition, the relaxation time is critical to electric displacements of a thermal wave mode, but is not essential for those of Lamb-like modes. The results can be used for the optimization of thermo-electric-elastic coupling structures.
Źródło:
Archives of Mechanics; 2023, 75, 1-2; 3-26
0373-2029
Pojawia się w:
Archives of Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Signal Subspace Speech Enhancement Approach Based on Joint Low-Rank and Sparse Matrix Decomposition
Autorzy:
Sun, C.
Xie, J.
Leng, Y.
Powiązania:
https://bibliotekanauki.pl/articles/177990.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
subspace speech enhancement
singular value decomposition
joint low-rank and sparse matrix decomposition
Opis:
Subspace-based methods have been effectively used to estimate enhanced speech from noisy speech samples. In the traditional subspace approaches, a critical step is splitting of two invariant subspaces associated with signal and noise via subspace decomposition, which is often performed by singular-value decomposition or eigenvalue decomposition. However, these decomposition algorithms are highly sensitive to the presence of large corruptions, resulting in a large amount of residual noise within enhanced speech in low signal-to-noise ratio (SNR) situations. In this paper, a joint low-rank and sparse matrix decomposition (JLSMD) based subspace method is proposed for speech enhancement. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank value for the underlying clean speech matrix. Then the subspace decomposition is performed by means of JLSMD, where the decomposed low-rank part corresponds to enhanced speech and the sparse part corresponds to noise signal, respectively. An extensive set of experiments have been carried out for both of white Gaussian noise and real-world noise. Experimental results show that the proposed method performs better than conventional methods in many types of strong noise conditions, in terms of yielding less residual noise and lower speech distortion.
Źródło:
Archives of Acoustics; 2016, 41, 2; 245-254
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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