I would like to interpret problem on picture below, which is about perceptron learning. It is about supervised learning wiht a training set, so correctness of values should be checked against a predefined set of values. I don't exactly know, how A, B and bias(b) values come. Could you please explain meaning of these and how these computed and changed during the learning process?
Here you have an intuitive, visual, interactive and beautiful guide to the basics concepts of neural networks: https://jalammar.github.io/visual-interactive-guide-basics-neural-networks/
It will problably solve all your doubts. However, if you still have more questions after the reading, you will be able to ask something more specific. Enjoy!