Local minima in Backpropagation algorithm

Question

The addition of an extra term, called a proportional factor reduces the convergence of the back propagation algorithm. So how to avoid local minima in Back propagation algorithm.

Answer 1

In local minimum a gradient of an error function is a zero vector - so backprop - which is using a gradient - cannot move your parameters any further and finishes training.