Confusions about hopfield neural network solved example!

I am from Nepal and instead of asking us code, these are types of questions that are asked in our country examination system.

IDK what's their purpose. But some of them are badly hard as there are not many examples about it in textbook(In Nepal we can't get the textbook reference that the syllabus is made upon, we can of course get international writers textbook but our syllabus and exam paper is based on Indian author textbooks and we don't get that here in Nepal)

So I was studying about hopfield network and got badly confused. I have listed my confusions with annonations. It is not like I don't understand anything, I do understand the gist, but I am not very clear about each and every concepts.

And I didn't even find proper resources to study this topics in reference to our exam in internet as well.


https://imgur.com/a/bWzz011


Source-:

 

I found this for you:
Hopfield network is a special kind of neural network whose response is different from other neural networks. It is calculated by converging iterative process. It has just one layer of neurons relating to the size of the input and output, which must be the same.
In a Hopfield network, all the nodes are inputs to each other, and they're also outputs. As I stated above, how it works in computation is that you put a distorted pattern onto the nodes of the network, iterate a bunch of times, and eventually it arrives at one of the patterns we trained it to know and stays there.

here is an example:

http://web.cs.ucla.edu/~rosen/161/notes/hopfield.html

 

I actually have solved example. Problem is I am not understanding it.