The SPRANNLIB user guide

• Introduction to SPRANNLIB
  • Introduction
  • System requirements
  • SPRANNLIB implementation
  • Overview of the manual
• Statistical pattern recognition library
  • Important data structures
    • Vectors and matrices
    • Data sets
  • Important support functions in SPRLIB
    • Additional matrix and vector functions
    • Supporting data set functions
  • Pattern recognition algorithms in SPRLIB
• Artificial neural network library
  • Considerations on Network Representation
  • Implementation
    • The top level network data structure
    • The unit structure
    • The link data structure
    • The weight structure
    • The unit value structure
  • Functions and Algorithms
    • Considerations on functions and algorithms
    • Supporting network functions
      • Low level supporting functions
      • High level supporting functions
  • Learning algorithms
    • Feed forward networks
    • Kohonen networks
• Tools
  • Interfacing to other software packages
  • Backpropagation program
  • Generic application set-up
• An example application