Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Qingquan Chang"'
Publikováno v:
Известия Российской академии наук. Серия математическая. 87:161-210
Детально изучена динамика слабо диссипативных волновых уравнений в ограниченных трехмерных областях в случае, когда коэффициент дисси
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f40018c197352ef8a84f6c4965190bfa
https://doi.org/10.4213/im9250
https://doi.org/10.4213/im9250
Publikováno v:
Discrete & Continuous Dynamical Systems - B. 25:2793-2824
We study the asymptotic behavior of solutions of a stochastic time-dependent damped wave equation. With the critical growth restrictions on the nonlinearity \begin{document}$ f $\end{document} and the time-dependent damped term, we prove the global e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b8f04d161c95e1c135fc060ea52e680e
https://doi.org/10.3934/dcdsb.2020033
https://doi.org/10.3934/dcdsb.2020033
Autor:
Qingquan Chang, Dandan Li
Publikováno v:
Journal of Mathematical Physics. 64:022702
We investigate the longtime dynamical behavior of 2D Navier–Stokes equations with a moving boundary. We obtain the well-posedness and dissipation through the penalty method. Then, we derive the regularity by applying a new penalty. Finally, we show
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6de02e9fb3bde1f461e16f9f8c3b3b6d
https://doi.org/10.1063/5.0113626
https://doi.org/10.1063/5.0113626
Publikováno v:
Computers & Mathematics with Applications. 77:2407-2431
In this paper we consider the long-time behavior of a class of stochastic degenerate parabolic equations involving an operator which is X -elliptic with respect to a family of locally Lipschitz continuous vector fields X = { X 1 , X 2 , … , X m ˜
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::16635a4c7abc0bf6c31c2e1682cdab51
https://doi.org/10.1016/j.camwa.2018.12.023
https://doi.org/10.1016/j.camwa.2018.12.023
Autor:
Qingquan Chang, Dandan Li
Publikováno v:
Journal of Mathematical Physics. 63:052702
We explore the convergence of the global attractors for a class of perturbed severely damped wave equations with the Dirichlet boundary condition in the 3D bounded domain. With respect to the perturbation parameter, it is shown that the global attrac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e1ea9bfaabd9457e99fc3df489b96ba1
https://doi.org/10.1063/5.0080012
https://doi.org/10.1063/5.0080012
Publikováno v:
Nonlinear Analysis: Real World Applications. 63:103421
The aim of this paper is to analyze the long-time dynamical behavior of the solution for a degenerate wave equation with time-dependent damping term ∂ t t u + β ( t ) ∂ t u = L u ( x , t ) + f ( u ) on a bounded domain Ω ⊂ R N with Dirichlet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63e23220d4b2f9ba459b5927d49860bc
https://doi.org/10.1016/j.nonrwa.2021.103421
https://doi.org/10.1016/j.nonrwa.2021.103421
Publikováno v:
Journal of Mathematical Analysis and Applications. 453:1-19
The aim of this paper is to consider a class of degenerate damped hyperbolic equations with the critical nonlinearity involving an operator L that is X -elliptic with respect to a family of vector fields X . We prove the global existence of solutions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::303fbc3620baf081307b4a183c1f93c0
https://doi.org/10.1016/j.jmaa.2017.03.077
https://doi.org/10.1016/j.jmaa.2017.03.077
Publikováno v:
Information Sciences. 381:250-269
In this paper, a new variant of feedforward neural networks has been proposed for a class of nonsmooth optimization problems. The penalty term of the presented neural networks stems from the Group Lasso method which selects hidden variables in a grou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f269016155cc434d14e97cb1c2b9739
https://doi.org/10.1016/j.ins.2016.11.020
https://doi.org/10.1016/j.ins.2016.11.020
Publikováno v:
IEEE transactions on cybernetics. 49(12)
The application and theoretical analysis of fault tolerant learning are very important for neural networks. Our objective here is to realize fault tolerant sparse multilayer perceptron (MLP) networks. The stochastic gradient descent method has been e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd63cc9c002b473a30ee2da69c0e8caf
https://pubmed.ncbi.nlm.nih.gov/30530381
https://pubmed.ncbi.nlm.nih.gov/30530381