Why will both the Delta Rule and back propagation continue to have some error, whereas the Perceptron Learning Rule halts when there is no error present?
What is the difference between offline and batch training?
What are the differences between biological and artificial neurons (neural networks) in terms of both structure and functionality?
The human brain consists of between 10 billion (1010) and 100 billion (1011) neurons. Once we understand the workings of the human brain 1 and we construct full-scale software and/or hardware simulations, what do you predict will occur?
What information does the dot product of x with w provide in an ANN?
How is this information used in the following:
a. The Perceptron Learning Rule?
b. The Delta Rule?
c. Back propagation?
The back propagation algorithm is often referred to as the generalized Delta Rule. Why do you think this is so?