I got to this part:

What I don't understand is how and why does this addition happen? How does the logic flow in this case? Why do you add together only the negative numbers? Having a hard time visualizing this logic.-snip-

We must now compare those weights with the input pattern of 0101:

0 1 0 1

0 -1 1 -1We will sum only the weights corresponding to the positions that contain a 1 in the input pattern. Therefore, the activation of the first neuron is –1 + –1, or –2. The results of the activation of each neuron are shown below.

N1 = -1 + -1 = -2

N2 = 0 + 1 = 1

N3 = -1 + -1 = -2

N4 = 1 + 0 = 1

Therefore, the output neurons, which are also the input neurons, will report the above activation results. The final output vector will then be –2, 1, –2, 1. These val- ues are meaningless without an activation function. We said earlier that a threshold establishes when a neuron will fire. A threshold is a type of activation function. An activation function determines the range of values that will cause the neuron, in this case the output neuron, to fire. A threshold is a simple activation function that fires when the input is above a certain value.

-snip-

If anyone could provide some input, I'd greatly appreciate it.

The part that's causing me to scratch my head is on page 88 of the book, if that helps.

**Edited by ysg, 02 May 2013 - 08:27 AM.**