17 resultados para Véu
em Bulgarian Digital Mathematics Library at IMI-BAS
Resumo:
A generalized convolution with a weight function for the Fourier cosine and sine transforms is introduced. Its properties and applications to solving a system of integral equations are considered.
Resumo:
Mathematics Subject Classification: Primary 33E20, 44A10; Secondary 33C10, 33C20, 44A20
Resumo:
Mathematics Subject Classification: 44A05, 44A35
Resumo:
This paper concerns the application of recent information technologies for creating a software system for numerical simulations in the domain of plasma physics and in particular metal vapor lasers. The presented work is connected with performing modernization of legacy physics software for reuse on the web and inside a Service-Oriented Architecture environment. Applied and described is the creation of Java front-ends of legacy C++ and FORTRAN codes. Then the transformation of some of the scientific components into web services, as well as the creation of a web interface to the legacy application, is presented. The use of the BPEL language for managing scientific workflows is also considered.
Resumo:
MSC 2010: 26A33, 33E12, 34K29, 34L15, 35K57, 35R30
Resumo:
2000 Mathematics Subject Classification: 62G08, 62P30.
Resumo:
2000 Mathematics Subject Classification: 60J80.
Resumo:
2000 Mathematics Subject Classification: 60G70, 60F12, 60G10.
Resumo:
2000 Mathematics Subject Classi cation: 60J80.
Resumo:
2000 Mathematics Subject Classification: 60G70, 60G18.
Resumo:
2000 Mathematics Subject Classification: 05A16, 05A17.
Resumo:
2000 Mathematics Subject Classification: 60J80, 62P05.
Resumo:
2000 Mathematics Subject Classification: 60J80.
Resumo:
There are limitations in recent research undertaken on attribute reduction in incomplete decision systems. In this paper, we propose a distance-based method for attribute reduction in an incomplete decision system. In addition, we prove theoretically that our method is more effective than some other methods.
Resumo:
A rough set approach for attribute reduction is an important research subject in data mining and machine learning. However, most attribute reduction methods are performed on a complete decision system table. In this paper, we propose methods for attribute reduction in static incomplete decision systems and dynamic incomplete decision systems with dynamically-increasing and decreasing conditional attributes. Our methods use generalized discernibility matrix and function in tolerance-based rough sets.