Introduction to Neural Networks with Java

Introduction to Neural Networks in Java introduces the Java programmer to the world of Neural Networks and Artificial Intelligence. Neural network architectures such as the feedforward backpropagation, Hopfield, and Kohonen networks are discussed. Additional AI topics, such as Genetic Algorithms and Simulated Annealing, are also introduced.

Practical examples are given for each neural network. Examples include the Traveling Salesman problem, handwriting recognition, fuzzy logic and learning mathematical functions. All Java source code can be downloaded online. In addition to showing the programmer how to construct these neural networks, the book discusses the Java Object Oriented Neural Engine (JOONE). JOONE is a free open source Java neural engine.

Jeff Heaton is an author, college instructor, and consultant. Jeff lives in Chesterfield (St. Louis), Missouri. The author of four books and over two dozen journal and magazine articles, Jeff specializes in Internet, socket-level/spidering and Artificial Intelligence programming. A Sun Certified Java Programmer and a Senior IEEE Member Jeff holds a Masters Degree in Information Management from Washington University in St. Louis.