Interdisciplinary Computing in Java Programming

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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.

Author(s): Sun-Chong Wang (auth.)
Series: The Springer International Series in Engineering and Computer Science 743
Edition: 1
Publisher: Springer US
Year: 2003

Language: English
Pages: 266
Tags: Theory of Computation; Systems Theory, Control; Artificial Intelligence (incl. Robotics); Calculus of Variations and Optimal Control; Optimization; Programming Languages, Compilers, Interpreters

Front Matter....Pages i-xii
Front Matter....Pages 1-1
Java Basics....Pages 3-15
Graphical and Interactive Java....Pages 17-37
High Performance Computing....Pages 39-55
Front Matter....Pages 57-57
Simulated Annealing....Pages 59-79
Artificial Neural Network....Pages 81-100
Genetic Algorithm....Pages 101-116
Monte Carlo Simulation....Pages 117-131
Molecular Dynamics....Pages 133-145
Cellular Automata....Pages 147-165
Path Integral....Pages 167-180
Data Fitting....Pages 181-194
Bayesian Analysis....Pages 195-210
Graphical Model....Pages 211-239
JNI Technology....Pages 241-252
Back Matter....Pages 253-266