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|a 9783540284383
|9 978-3-540-28438-3
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|a 003.3
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|a Automatic Differentiation: Applications, Theory, and Implementations
|h [electronic resource] /
|c edited by H. Martin Bücker, George Corliss, Paul Hovland, Uwe Naumann, Boyana Norris.
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|a 1st ed. 2006.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2006.
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|a XVIII, 370 p. 108 illus.
|b online resource.
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|a text
|b txt
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|a computer
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|a text file
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|a Lecture Notes in Computational Science and Engineering,
|x 2197-7100 ;
|v 50
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|a Perspectives on Automatic Differentiation: Past, Present, and Future? -- Backwards Differentiation in AD and Neural Nets: Past Links and New Opportunities -- Solutions of ODEs with Removable Singularities -- Automatic Propagation of Uncertainties -- High-Order Representation of Poincarée Maps -- Computation of Matrix Permanent with Automatic Differentiation -- Computing Sparse Jacobian Matrices Optimally -- Application of AD-based Quasi-Newton Methods to Stiff ODEs -- Reduction of Storage Requirement by Checkpointing for Time-Dependent Optimal Control Problems in ODEs -- Improving the Performance of the Vertex Elimination Algorithm for Derivative Calculation -- Flattening Basic Blocks -- The Adjoint Data-Flow Analyses: Formalization, Properties, and Applications -- Semiautomatic Differentiation for Efficient Gradient Computations -- Computing Adjoints with the NAGWare Fortran 95 Compiler -- Transforming Equation-Based Models in Process Engineering -- Extension of TAPENADE toward Fortran 95 -- A Macro Language for Derivative Definition in ADiMat -- Simulation and Optimization of the Tevatron Accelerator -- Periodic Orbits of Hybrid Systems and Parameter Estimation via AD -- Implementation of Automatic Differentiation Tools for Multicriteria IMRT Optimization -- Application of Targeted Automatic Differentiation to Large-Scale Dynamic Optimization -- Automatic Differentiation: A Tool for Variational Data Assimilation and Adjoint Sensitivity Analysis for Flood Modeling -- Development of an Adjoint for a Complex Atmospheric Model, the ARPS, using TAF -- Tangent Linear and Adjoint Versions of NASA/GMAO's Fortran 90 Global Weather Forecast Model -- Efficient Sensitivities for the Spin-Up Phase -- Streamlined Circuit Device Model Development with fREEDAR® ãnd ADOL-C -- Adjoint Differentiation of a Structural Dynamics Solver -- A Bibliography of Automatic Differentiation.
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|a Mathematics-Data processing.
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|a Software engineering.
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|a Mathematical analysis.
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|a Electrical engineering.
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|a Computer science-Mathematics.
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|a Computational Science and Engineering.
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|a Software Engineering.
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|a Analysis.
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|a Electrical and Electronic Engineering.
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|a Computational Mathematics and Numerical Analysis.
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| 650 |
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|a Mathematics of Computing.
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| 700 |
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|a Bücker, H. Martin.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 700 |
1 |
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|a Corliss, George.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 700 |
1 |
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|a Hovland, Paul.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 700 |
1 |
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|a Naumann, Uwe.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 700 |
1 |
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|a Norris, Boyana.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer Nature eBook
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| 776 |
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|i Printed edition:
|z 9783540814580
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| 776 |
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|i Printed edition:
|z 9783540284031
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| 830 |
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|a Lecture Notes in Computational Science and Engineering,
|x 2197-7100 ;
|v 50
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| 856 |
4 |
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|u https://doi.uam.elogim.com/10.1007/3-540-28438-9
|z Texto Completo
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|a ZDB-2-SMA
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|a ZDB-2-SXMS
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|a Mathematics and Statistics (SpringerNature-11649)
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|a Mathematics and Statistics (R0) (SpringerNature-43713)
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