Java number cruncher : the Java programmer's guide to numerical computing

Java Number Cruncher: The Java Programmer's Guide to Numerical Computing , by topic expert Ronald Mak, provides practical information for Java programmers who write mathematical programs. Without excessive mathematical theory, he animates the algorithms on the computer screen with interactive graphical programs and applets

• Non-theoretical explanations of practical numerical algorithms
• Algorithms in action with animated, interactive graphical Java programs and applets
• Computational errors and how to remove them from your code

Understand "computer math" and get the numbers you expect, reliably.

In Java Number Cruncher, author Ronald Mak explains how to spot-and how to avoid-the subtle programming miscues that can cause vexing calculation errors in your applications. An authority on mapping pure math to computer math, he explains how to use the often-overlooked computational features of Java, and does so in a clear, non-theoretical style.

Without getting lost in mathematical detail, you'll learn practical numerical algorithms for safely summing numbers, finding roots of equations, interpolation and approximation, numerical integration, solving differential equations, matrix operations, and solving sets of simultaneous equations. You'll also enjoy intriguing topics such as searching for patterns in prime numbers, generating random numbers, computing thousands of digits of pi, and creating intricately beautiful fractal images.

Java Number Cruncher includes:

• Practical information all Java programmers should know
• Popular computational algorithms in Java-without excessive mathematical theory
• Interactive graphical programs that bring the algorithms to life on the computer screen
• Rounding errors, the pitfalls of integer arithmetic, Java's implementation of the IEEE 754 floating-point standard, and more

This book is useful to all Java programmers, especially for those who want to learn about numerical computation, and for developers of scientific, financial, and data analysis applications.