In some cases, an auto-associative net does not reproduce a stored pattern the first time around, but if the result of the first showing is input to the net again, the stored pattern is reproduced.
Hopfield networks serve as content-addressable ("associative") memory systems with binary threshold nodes, and they have been shown to act as autoassociative since they are capable of remembering data by observing a portion of that data.
For example: It is possible that the associative recall is a transformation from the pattern “banana” to the different pattern “monkey.”[6] Bidirectional associative memories (BAM)[7] are artificial neural networks that have long been used for performing heteroassociative recall.
For example, the sentence fragments presented below are sufficient for most English-speaking adult humans to recall the missing information.
Many readers will realize the missing information is in fact: This demonstrates the capability of autoassociative networks to recall the whole by using some of its parts.