Multiple Back-Propagation

Tutorial

  1. Introduction (includes the MBP Algorithm)
  2. Creating the training and the test datasets
  3. Defining the topology of the neural networks
  4. Configuring the activation functions of the neurons
  5. Defining the neural network learning configuration
  6. Training a neural network - Part I (regression)
  7. Training a neural network - Part II (classification)
  8. Copying data and graphics
  9. Initialize, view, save and load the neural network weights
  10. Load and save a neural network
  11. Generate C code from a trained neural network
  12. Analyzing the input sensitivity of a neural network
Multiple Back-Propagation free software (MBP). MBP can train both backpropagation and multiple back propagation neural networks.