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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

[QUOTE="MathLover1, post: 1099931, member: 280"] 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,[B] all the nodes are inputs to each other, and they're also outputs.[/B] 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: [URL]http://web.cs.ucla.edu/~rosen/161/notes/hopfield.html[/URL] [/QUOTE]