The Hopfield network is used to store or rebuild patterns. The algorithm of this network consists of two phases as follows
A) Storage phase:
In this phase, we want to store patterns in the network so that these patterns would be steady state.
B) Recovery phase
In this phase, the experimental vector x (which is original pattern with noise) is applied to the network, and we expect the network to give us the desired pattern with respect to the weights obtained in the storage phase.
You can download project report with matlab codes below:
Hebb and MLP Neural network is also used in this project and they are included in the report below.