I am currently learning the concept of neural networks by myself. I am working with a very good pdf from http://neuralnetworksanddeeplearning.com/chap1.html
I also did a few exercises but there is one exercise I really don't understand.
Task: There is a way of determining the bitwise representation of a digit by adding an extra layer to the three-layer network above. The extra layer converts the output from the previous layer into a binary representation, as illustrated in the figure below. Find a set of weights and biases for the new output layer. Assume that the first 3 layers of neurons are such that the correct output in the third layer (i.e., the old output layer) has activation at least 0.99, and incorrect outputs have activation less than 0.01. I found also the solution, as can be seen in the second image
I understand why the matrix has to have this shape, but I really struggle to understand the step, where the user calculates
0.99 + 3*0.01 4*0.01
PS: I know that the question was answered in Extra output layer in a neural network (Decimal to binary). However, the specific step I am looking for was not answered.