Training

Modes

Sequential

• Apply changes after each train pattern
• Less local storage for each synaptic connection
• Search in weight space stochastic
  • Patterns presented to network in random order
  • Less likely to fall into local minima
• Difficult to establish theoretical conditions for convergence

Batch

• Apply changes at the end
• Accurate estimate of gradient vector
• Can guarantee convergence to local minimum