ISBN13: | 9783540213192 |
ISBN10: | 3540213198 |
Kötéstípus: | Keménykötés |
Terjedelem: | 384 oldal |
Méret: | 235x155 mm |
Súly: | 844 g |
Nyelv: | angol |
Illusztrációk: | XV, 384 p. Tables, black & white |
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Matematika a mérnöki- és természettudományok területén
A mérnöki tudományok általános kérdései
Mesterséges intelligencia
A fizika általános kérdései
Mechanika
Gázok fizikája
Kvantumfizika (kvantummechanika)
További könyvek a fizika területén
Matematika a mérnöki- és természettudományok területén (karitatív célú kampány)
A mérnöki tudományok általános kérdései (karitatív célú kampány)
Mesterséges intelligencia (karitatív célú kampány)
A fizika általános kérdései (karitatív célú kampány)
Mechanika (karitatív célú kampány)
Gázok fizikája (karitatív célú kampány)
Kvantumfizika (kvantummechanika) (karitatív célú kampány)
További könyvek a fizika területén (karitatív célú kampány)
Conjugate Gradient Algorithms and Finite Element Methods
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The position taken in this collection of pedagogically written essays is that conjugate gradient algorithms and finite element methods complement each other extremely well. Via their combinations practitioners have been able to solve differential equations and multidimensional problems modeled by ordinary or partial differential equations and inequalities, not necessarily linear, optimal control and optimal design being part of these problems. The aim of this book is to present both methods in the context of complicated problems modeled by linear and nonlinear partial differential equations, to provide an in-depth discussion on their implementation aspects. The authors show that conjugate gradient methods and finite element methods apply to the solution of real-life problems. They address graduate students as well as experts in scientific computing.
The position taken in this collection of pedagogically written essays is that conjugate gradient algorithms and finite element methods complement each other extremely well.
Via their combinations practitioners have been able to solve complicated, direct and inverse, multidemensional problems modeled by ordinary or partial differential equations and inequalities, not necessarily linear, optimal control and optimal design being part of these problems.
The aim of this book is to present both methods in the context of complicated problems modeled by linear and nonlinear partial differential equations, to provide an in-depth discussion on their implementation aspects. The authors show that conjugate gradient methods and finite element methods apply to the solution of real-life problems. They address graduate students as well as experts in scientific computing.