Utvidet returrett til 31. januar 2025

Topological Data Analysis for Scientific Visualization

Om Topological Data Analysis for Scientific Visualization

Combining theoretical and practical aspects of topology, this book provides a comprehensive and self-contained introduction to topological methods for the analysis and visualization of scientific data. Theoretical concepts are presented in a painstaking but intuitive manner, with numerous high-quality color illustrations. Key algorithms for the computation and simplification of topological data representations are described in detail, and their application is carefully demonstrated in a chapter dedicated to concrete use cases. With its fine balance between theory and practice, "Topological Data Analysis for Scientific Visualization" constitutes an appealing introduction to the increasingly important topic of topological data analysis for lecturers, students and researchers.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9783319715063
  • Bindende:
  • Hardback
  • Sider:
  • 150
  • Utgitt:
  • 29. januar 2018
  • Utgave:
  • 12017
  • Dimensjoner:
  • 161x241x16 mm.
  • Vekt:
  • 398 g.
  • BLACK NOVEMBER
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 21. desember 2024
Utvidet returrett til 31. januar 2025

Beskrivelse av Topological Data Analysis for Scientific Visualization

Combining theoretical and practical aspects of topology, this book provides a comprehensive and self-contained introduction to topological methods for the analysis and visualization of scientific data.
Theoretical concepts are presented in a painstaking but intuitive manner, with numerous high-quality color illustrations. Key algorithms for the computation and simplification of topological data representations are described in detail, and their application is carefully demonstrated in a chapter dedicated to concrete use cases.
With its fine balance between theory and practice, "Topological Data Analysis for Scientific Visualization" constitutes an appealing introduction to the increasingly important topic of topological data analysis for lecturers, students and researchers.

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