Numerical and Symbolic Scientific Computing: Progress and Prospects

Author:   Ulrich Langer ,  Peter Paule
Publisher:   Springer Verlag GmbH
Edition:   2012
Volume:   1
ISBN:  

9783709107935


Pages:   358
Publication Date:   19 November 2011
Format:   Paperback
Availability:   Awaiting stock   Availability explained
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Numerical and Symbolic Scientific Computing: Progress and Prospects


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Author:   Ulrich Langer ,  Peter Paule
Publisher:   Springer Verlag GmbH
Imprint:   Springer Verlag GmbH
Edition:   2012
Volume:   1
Dimensions:   Width: 15.50cm , Height: 2.30cm , Length: 23.50cm
Weight:   0.563kg
ISBN:  

9783709107935


ISBN 10:   3709107938
Pages:   358
Publication Date:   19 November 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Awaiting stock   Availability explained
The supplier is currently out of stock of this item. It will be ordered for you and placed on backorder. Once it does come back in stock, we will ship it out for you.

Table of Contents

Fast solvers and a posteriori error estimates in elastoplasticity. - Symbolic analysis for boundary problems: from rewriting to parametrized Groebner Bases. - approximate implicitization of space curves. - A symbolic-numeric algorithm for genus computation. - Linear partial differential equations and linear partial differential operators in computer algebra. - Computer algebra meets finite elements: an efficient implementation for Maxwell's Equations. - Sound and compelte verificcation condition generator for functional recursive programs. - Analytical evaluations of double integral expressions related to total variation. - A symbolic approach to generation and analysis of finite difference schemes of partial differential equations. - The Seven Dwarfs of symbolic computation. - An introduction to automated discovery in geometry through symbolic computation. - White noise analysis for stochastic partial differential equations. - Computing smoothing rates of collective point smoothers for optimal control problems using symbolic computation. - Sparsity optimized high-order finite element functions on simplices.

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