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  • Sprache: Englisch

    Verlag: Springer, 2012

    3642300227 / 9783642300226

    Serie: Buch 63 von 111 - Lecture Notes in Computational Science and Engineering

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    EUR 128,11

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    Zustand: New. In English.

  • Sprache: Englisch

    Verlag: Springer, 2014

    3642439918 / 9783642439919

    Serie: Buch 63 von 111 - Lecture Notes in Computational Science and Engineering

    • Softcover

    Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections

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    Zustand: New. In English.

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    Sprache: Englisch

    Verlag: Springer, 2014

    3642439918 / 9783642439919

    Serie: Buch 63 von 111 - Lecture Notes in Computational Science and Engineering

    • Softcover

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    Taschenbuch. Zustand: Neu. Recent Advances in Algorithmic Differentiation | Shaun Forth (u. a.) | Taschenbuch | Lecture Notes in Computational Science and Engineering | xviii | Englisch | 2014 | Springer | EAN 9783642439919 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Sprache: Englisch

    Verlag: Springer Verlag, 2012

    3642300227 / 9783642300226

    Serie: Buch 63 von 111 - Lecture Notes in Computational Science and Engineering

    • Hardcover

    Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books

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    EUR 157,32

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    Hardcover. Zustand: Brand New. 2012 edition. 353 pages. 9.25x6.25x1.00 inches. In Stock.

  • Sprache: Englisch

    Verlag: Springer, 2014

    3642439918 / 9783642439919

    Serie: Buch 63 von 111 - Lecture Notes in Computational Science and Engineering

    • Softcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The proceedings represent the state of knowledge in the area of algorithmic differentiation (AD). The 31 contributed papers presented at the AD2012 conference cover the application of AD to many areas in science and engineering as well as aspects of AD theory and its implementation in tools. For all papers the referees, selected from the program committee and the greater community, as well as the editors have emphasized accessibility of the presented ideas also to non-AD experts. In the AD tools arena new implementations are introduced covering, for example, Java and graphical modeling environments or join the set of existing tools for Fortran. New developments in AD algorithms target the efficiency of matrix-operation derivatives, detection and exploitation of sparsity, partial separability, the treatment of nonsmooth functions, and other high-level mathematical aspects of the numerical computations to be differentiated. Applications stem from the Earth sciences, nuclear engineering, fluid dynamics, and chemistry, to name just a few. In many cases the applications in a given area of science or engineering share characteristics that require specific approaches to enable AD capabilities or provide an opportunity for efficiency gains in the derivative computation. The description of these characteristics and of the techniques for successfully using AD should make the proceedings a valuable source of information for users of AD tools.

  • Sprache: Englisch

    Verlag: Springer Spektrum, 2012

    3642300227 / 9783642300226

    Serie: Buch 63 von 111 - Lecture Notes in Computational Science and Engineering

    • Hardcover

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The proceedings represent the state of knowledge in the area of algorithmic differentiation (AD). The 31 contributed papers presented at the AD2012 conference cover the application of AD to many areas in science and engineering as well as aspects of AD theory and its implementation in tools. For all papers the referees, selected from the program committee and the greater community, as well as the editors have emphasized accessibility of the presented ideas also to non-AD experts. In the AD tools arena new implementations are introduced covering, for example, Java and graphical modeling environments or join the set of existing tools for Fortran. New developments in AD algorithms target the efficiency of matrix-operation derivatives, detection and exploitation of sparsity, partial separability, the treatment of nonsmooth functions, and other high-level mathematical aspects of the numerical computations to be differentiated. Applications stem from the Earth sciences, nuclear engineering, fluid dynamics, and chemistry, to name just a few. In many cases the applications in a given area of science or engineering share characteristics that require specific approaches to enable AD capabilities or provide an opportunity for efficiency gains in the derivative computation. The description of these characteristics and of the techniques for successfully using AD should make the proceedings a valuable source of information for users of AD tools.

  • Sprache: Englisch

    Verlag: Springer, 2012

    3642300227 / 9783642300226

    Serie: Buch 63 von 111 - Lecture Notes in Computational Science and Engineering

    • Hardcover

    Anbieter: Buchpark, Trebbin, DeutschlandBuchpark

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    EUR 83,61

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    Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 380 | Sprache: Englisch | Produktart: Bücher | The proceedings represent the state of knowledge in the area of algorithmic differentiation (AD). The 31 contributed papers presented at the AD2012 conference cover the application of AD to many areas in science and engineering as well as aspects of AD theory and its implementation in tools. For all papers the referees, selected from the program committee and the greater community, as well as the editors have emphasized accessibility of the presented ideas also to non-AD experts. In the AD tools arena new implementations are introduced covering, for example, Java and graphical modeling environments or join the set of existing tools for Fortran. New developments in AD algorithms target the efficiency of matrix-operation derivatives, detection and exploitation of sparsity, partial separability, the treatment of nonsmooth functions, and other high-level mathematical aspects of the numerical computations to be differentiated. Applications stem from the Earth sciences, nuclear engineering, fluid dynamics, and chemistry, to name just a few. In many cases the applications in a given area of science or engineering share characteristics that require specific approaches to enable AD capabilities or provide an opportunity for efficiency gains in the derivative computation. The description of these characteristics and of the techniques for successfully using AD should make the proceedings a valuable source of information for users of AD tools.