Introduces the operations and application of neural networks in the context of
Mathematica's programming language. Shows professionals and students how to use
Mathematica to simulate neural network operations and to assess neural network behavior and performance. The electronic supplement provides the source code for the programs in the book.
Introduction to Neural Networks and
Mathematica | Training by Error Minimization | Backpropagation and Its Variants | Optimization and Constraint Satisfaction | Feedback and Recurrent Networks | Adaptive Resonance Theory | Genetic Algorithms
Computer Science
