Why is the hopfield network a model of associative memory? I'm struggling to understand the meaning of the term associative memory in the context of Hopfield networks. I'm not sure if associative learning is the same thing or a different thing. In associative learning, you have two unrelated items and you learn to associate one item with the other. In a hopfield network you have a partial pattern then you can retrieve the full pattern. How is this associative learning? Or are associative learning and associative memory different things?
An Associative Memory is a synonym for Content Addressable Memory or a memory which stores the result of associative learning, wherein an input item is learned to be associated with an output item.

A Hopfield network is a type of associative memory, wherein an input item (including partial, noisy representations of the original trained/encoded item) is an associated to a the ideal representation of the trained/desired/encoded input item.

For further discussion of Hopfield networks, I recommend look at the question "What&#39;s the difference between a Hamming and Hopfield network?"