Practical Implementation Issues

This section is intended as a guide to the program components section and addresses the practical aspects of using JETNET 3.0. We include information on all new features of JETNET 3.0 and on those in the earlier version that generated questions from the users. All subroutines, parameters and switches mentioned here are described in the program components section.

In some rare cases we mention techniques that are not part of the JETNET 3.0 package. This is because we consider them important, although we have not had the opportunity to implement them, and because the JETNET 3.0 user should be aware of their existence.

• Initialization
  • Initial weight values
  • Backpropagation
  • Manhattan
  • Langevin
  • Quickprop
  • Conjugate Gradient
  • Rprop
  • Batch training
• Training the Network
• Dynamic Learning Parameters
• Conjugate Gradient Learning
  • The line search
• Output
• Pruning
• Computing the Hessian
• Receptive Fields and Shared Weights
• The Saturation Measure
• Limited Precision - Hardware Implementations