The Back-Propagation Algorithm as described in this guide/introduction is confusing, the final formula generated for del(w)(change in weights) is
del(wji) - Change in weights of synapse from j to i;
eta (n) - learning factor;
Oj - Output of previous layer j;
dj - Desired output from previous layer j;
xi - Input
I have few doubts associated with the formula.
What is the desired output for hidden layer and Input layer??
What is the j and i notation?
What should be the learning factor how can I decide(or generate) the value of learning factor i.e eta(n)?
Note: I want it to work like this (there would be differences in some factors but formulations should be similar..I cannot see any similarity in the formulations).