Hopfield networks

Hopfield network

Hopfield net consists of a number of nodes, each connected to every other node: it is a fully-connected network.

Hopfield net is a symmetrically-weighted network, since the weights on the link from one node to another are the same in both directions.

Each node has, like the single-layer perceptron, a threshold and a step-function. The nodes calculate the weighted sum of their inputs minus the threshold value, passing that through the step function to determine their output state.

The net takes only 2-state inputs-these can be binary (0,1) or bipolar (-1,+1).

Inputs to the network are applied to all nodes at once, and consist of a set of starting values, +1 or -1.

The output of the network is taken to be the value of all the nodes when the network has reached a stable, steady state.

Stochastic Hopfield network


The boltzmann machine