there is a very good explanation at StackExchange given by Gabrriel Romon Motivating sigmoid output units in neural networks starting with unnormalized log probabilities linear in $z=w^Th+b$ and $\phi(z)$

equation 6.22 can be rewritten into:

How to understand the equation 6.31 , and How does it derive from ?

I don't think so - the indices taken alone can be arbitrary (i.e. he could have written a,b,c or x,y,z for the indices of V). However when we are taking sums we need to ensure that the indices match.

In other words, I can say that V_x,y,z represent the ...

Could someone explain what the last sentence on page 342 means:

"In linear algebra notation, we index into arrays using 1 for the first entry"

I'm rather confused, because say if I wanted to find...

convolution

This is on page 342. In the first sentenced, j is referred to as a channel in the input. In the second sentence, j is refe...

In Chapter 7, Page 234, it says:

The new matrix is the same as the original one, but ...