Backpropagation on Time Scales

Overview

This section extends the previous section’s focus on the unified computational intelligence goal of developing the capability to adapt. The dynamic programming algorithm typically utilizes neural networks as function approximation tools. Therefore, discussing how to train a neural network within the unified framework of the time scales calculus contributes directly to this goal.

The results presented here are adapted from a paper that has been accepted for publication in IEEE Transactions on Neural Networks but that, at the time of this book’s completion, has not yet appeared.