Buch, Englisch, 266 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 429 g
Reihe: The Springer International Series in Engineering and Computer Science
Buch, Englisch, 266 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 429 g
Reihe: The Springer International Series in Engineering and Computer Science
ISBN: 978-1-4613-5046-0
Verlag: Springer US
Books on computation in the marketplace tend to discuss the topics within specific fields. Many computational algorithms, however, share common roots. Great advantages emerge if numerical methodologies break the boundaries and find their uses across disciplines. Interdisciplinary Computing In Java Programming Language introduces readers of different backgrounds to the beauty of the selected algorithms. Serious quantitative researchers, writing customized codes for computation, enjoy cracking source codes as opposed to the black-box approach. Most C and Fortran programs, despite being slightly faster in program execution, lack built-in support for plotting and graphical user interface. This book selects Java as the platform where source codes are developed and applications are run, helping readers/users best appreciate the fun of computation.
Interdisciplinary Computing In Java Programming Language is designed to meet the needs of a professional audience composed of practitioners and researchers in science and technology. This book is also suitable for senior undergraduate and graduate-level students in computer science, as a secondary text.
Zielgruppe
Professional/practitioner
Fachgebiete
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
Weitere Infos & Material
I Java Language.- 1. Java Basics.- 2. Graphical And Interactive Java.- 3. High Performance Computing.- II Computing.- 4. Simulated Annealing.- 5. Artificial Neural Network.- 6. Genetic Algorithm.- 7. Monte Carlo Simulation.- 8. Molecular Dynamics.- 9. Cellular Automata.- 10. Path Integral.- 11. Data Fitting.- 12. Bayesian Analysis.- 13. Graphical Model.- 14. Jni Technology.- Appendices.- A.- A.1 Web Computing.- A.2 Class Sources.- Inde.
