On a nonlocal singular mixed evolution problem.
Mesloub, Said, Lekrine, Nadia (2001)
Matematichki Vesnik
Similarity:
Mesloub, Said, Lekrine, Nadia (2001)
Matematichki Vesnik
Similarity:
S. Pyatkov (1992)
Banach Center Publications
Similarity:
In the first part of the paper we study some properties of eigenelements of linear selfadjoint pencils Lu = λBu. In the second part we apply these results to the investigation of some boundary value problems for mixed type second order operator-differential equations.
Nina A. Chernyavskaya, Leonid A. Shuster (2012)
Czechoslovak Mathematical Journal
Similarity:
Bouziani, Abdelfatah (2002)
International Journal of Mathematics and Mathematical Sciences
Similarity:
Bouziani, Abdelfatah (2002)
Abstract and Applied Analysis
Similarity:
Chen, Jiecheng, Li, Hongliang (2009)
Journal of Inequalities and Applications [electronic only]
Similarity:
Bouziani, Abdelfatah (2004)
International Journal of Mathematics and Mathematical Sciences
Similarity:
Miloš Zlámal (2001)
Applications of Mathematics
Similarity:
In part I of the paper (see Zlámal [13]) finite element solutions of the nonstationary semiconductor equations were constructed. Two fully discrete schemes were proposed. One was nonlinear, the other partly linear. In this part of the paper we justify the nonlinear scheme. We consider the case of basic boundary conditions and of constant mobilities and prove that the scheme is unconditionally stable. Further, we show that the approximate solution, extended to the whole time interval...
V. I. Kolyada (2006)
Banach Center Publications
Similarity:
We study mixed norm spaces that arise in connection with embeddings of Sobolev and Besov spaces. We prove Sobolev type inequalities in terms of these mixed norms. Applying these results, we obtain optimal constants in embedding theorems for anisotropic Besov spaces. This gives an extension of the estimate proved by Bourgain, Brezis and Mironescu for isotropic Besov spaces.
Merazga, Nabil, Bouziani, Abdelfatah (2003)
Abstract and Applied Analysis
Similarity: