Feedback Associative Memory Networks
The following figure shows a general configuration for a feedback neural
A feedback network needs many iteracions before retireven the final
pattern. The most popular feedback auto-association network is the Hopfield
model, which has the following characteristics:
In the follwing, a sequential (asynchronous) Hopfield
model and a parallel (synchronous) Hopfield
model will be introduced.
Synaptic weights (predetermined by the Hebbian rule or an energy function)
Nonlinear thresholding operations are used in each stage to produce binary-valued
State feedbacks are used so that states can be iteratively updated.
Iteractions will converge to a solution that minimizes an energy function
pertaining to the newtwork.
Sequential (asynchronous) Hopfield model
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Artificial Neural Networks