Interdisciplinary Computing in Java Programming
Author:   Sun-Chong Wang
Publisher:   Springer-Verlag New York Inc.
Edition:   2003 ed.
Volume:   743
ISBN:  

9781402075131


Pages:   266
Publication Date:   31 August 2003
Format:   Hardback
Availability:   In Print   Availability explained
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Interdisciplinary Computing in Java Programming


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Overview

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. This text 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 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.

Full Product Details

Author:   Sun-Chong Wang
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2003 ed.
Volume:   743
Dimensions:   Width: 15.50cm , Height: 1.70cm , Length: 23.50cm
Weight:   1.270kg
ISBN:  

9781402075131


ISBN 10:   1402075138
Pages:   266
Publication Date:   31 August 2003
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

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.

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